160 Commits

Author SHA1 Message Date
eugenefischer
b7c86f20b3 Add read depth attributes to graphml output 2022-09-28 03:01:52 -05:00
eugenefischer
3a47efd361 Update TODO 2022-09-28 03:01:03 -05:00
eugenefischer
58bb04c431 Remove redundant toString() calls 2022-09-28 02:08:17 -05:00
eugenefischer
610da68262 Refactor Vertex class to use SequenceRecords 2022-09-28 00:58:44 -05:00
eugenefischer
9973473cc6 Make serializable and implement getWellOccupancies method 2022-09-28 00:58:02 -05:00
eugenefischer
8781afd74c Reorder conditional 2022-09-28 00:57:06 -05:00
eugenefischer
88b6c79caa Refactor to simplify graph creation code 2022-09-28 00:07:59 -05:00
eugenefischer
35a519d499 update TODO 2022-09-27 22:20:57 -05:00
eugenefischer
5bd1e568a6 update TODO 2022-09-27 15:08:16 -05:00
eugenefischer
4ad1979c18 Add read depth simulation options to CLI 2022-09-27 15:05:50 -05:00
eugenefischer
423c9d5c93 Add read depth simulation options to CLI 2022-09-27 14:35:55 -05:00
eugenefischer
7c3c95ab4b update TODO in readme 2022-09-27 14:11:21 -05:00
eugenefischer
d71a99555c clean up metadata 2022-09-27 12:15:12 -05:00
eugenefischer
2bf2a9f5f7 Add comments 2022-09-27 11:51:51 -05:00
eugenefischer
810abdb705 Add read depth parameters to output metadata 2022-09-27 11:13:12 -05:00
eugenefischer
f7b3c133bf Add filtering based on occupancy/read count discrepancy 2022-09-26 23:39:18 -05:00
eugenefischer
14fcfe1ff3 spacing 2022-09-26 23:38:56 -05:00
eugenefischer
70fec95a00 Bug fix 2022-09-26 23:17:18 -05:00
eugenefischer
077af3b46e Clear plate in memory when simulating read depth 2022-09-26 23:17:10 -05:00
eugenefischer
db99c74810 Rework read depth simulation to allow edge weight calculations to work as expected. (This changes sample plate in memory, so caching the sample plate is incompatible) 2022-09-26 23:03:23 -05:00
eugenefischer
13a1af1f71 placeholder values until CLI is updated to support read depth simulation 2022-09-26 19:43:29 -05:00
eugenefischer
199c81f983 Implement read count for vertices 2022-09-26 19:42:19 -05:00
eugenefischer
19a2a35f07 Refactor plate assay methods to use maps passed as parameters rather than returning maps 2022-09-26 17:00:25 -05:00
eugenefischer
36c628cde5 Add code to simulate read depth 2022-09-26 16:52:56 -05:00
eugenefischer
1ddac63b0a Add exception handling 2022-09-26 14:28:35 -05:00
eugenefischer
e795b4cdd0 Add read depth option to interface 2022-09-26 14:25:47 -05:00
eugenefischer
60cf6775c2 notes toward command line read depth option 2022-09-26 14:25:30 -05:00
eugenefischer
8a8c89c9ba revert options menu 2022-09-26 14:24:58 -05:00
eugenefischer
86371668d5 Add menu option to activate simulation of read depth and sequence read errors 2022-09-26 13:47:19 -05:00
eugenefischer
d81ab25a68 Comment: need to update this when read count is implemented 2022-09-26 13:46:53 -05:00
eugenefischer
02c8e6aacb Refactor sequences to be strings instead of integers, to make simulating read errors easier 2022-09-26 13:37:48 -05:00
eugenefischer
f84dfb2b4b Method stub for simulating read depth 2022-09-26 00:43:13 -05:00
eugenefischer
184278b72e Add fields for simulating read depth. Also a priority queue for lookback auctions 2022-09-26 00:42:55 -05:00
eugenefischer
489369f533 Add flag to simulate read depth 2022-09-26 00:42:23 -05:00
eugenefischer
fbee591273 Change indentation 2022-09-25 22:36:02 -05:00
eugenefischer
603a999b59 Update readme 2022-09-25 22:35:52 -05:00
eugenefischer
c3df4b12ab Update readme with read depth TODO 2022-09-25 21:50:59 -05:00
eugenefischer
d1a56c3578 Hand-merge of some things from Dev_Vertex branch that didn't make it in for some reason 2022-09-25 19:07:25 -05:00
eugenefischer
16daf02dd6 Merge branch 'Dev_Vertex'
# Conflicts:
#	src/main/java/GraphModificationFunctions.java
#	src/main/java/GraphWithMapData.java
#	src/main/java/Simulator.java
#	src/main/java/Vertex.java
2022-09-25 18:33:26 -05:00
eugenefischer
04a077da2e update Readme 2022-09-25 18:24:12 -05:00
eugenefischer
740835f814 fix typo 2022-09-25 17:47:07 -05:00
eugenefischer
8a77d53f1f Output sequence counts before and after pre-filtering (currently pre-filtering only sequences present in all wells) 2022-09-25 17:20:50 -05:00
eugenefischer
58fa140ee5 add comments 2022-09-25 16:10:17 -05:00
eugenefischer
475bbf3107 Sort vertex lists by vertex label before making adjacency matrix 2022-09-25 15:54:28 -05:00
eugenefischer
4f2fa4cbbe Pre-filter saturating sequences only. Retaining singletons seems to improve matching accuracy in high sample rate test (well populations 10% of total cell sample size) 2022-09-25 15:19:56 -05:00
eugenefischer
58d418e44b Pre-filter saturating sequences only. Retaining singletons seems to improve matching accuracy in high sample rate test (well populations 10% of total cell sample size) 2022-09-25 15:06:46 -05:00
eugenefischer
1971a96467 Remove pre-filtering of singleton and saturating sequences 2022-09-25 14:55:43 -05:00
eugenefischer
e699795521 Revert "by-hand merge of needed code from custom vertex branch"
This reverts commit 29b844afd2.
2022-09-25 14:34:31 -05:00
eugenefischer
bd6d010b0b Revert "update TODO"
This reverts commit a054c0c20a.
2022-09-25 14:34:31 -05:00
eugenefischer
61d1eb3eb1 Revert "Reword output message"
This reverts commit 63317f2aa0.
2022-09-25 14:34:31 -05:00
eugenefischer
cb41b45204 Revert "Reword option menu item"
This reverts commit 06e72314b0.
2022-09-25 14:34:31 -05:00
eugenefischer
a84d2e1bfe Revert "Add comment on map data encodng"
This reverts commit 73c83bf35d.
2022-09-25 14:34:31 -05:00
eugenefischer
7b61d2c0d7 Revert "update version number"
This reverts commit e4e5a1f979.
2022-09-25 14:34:31 -05:00
eugenefischer
56454417c0 Revert "Restore pre-filtering of singleton and saturating sequences"
This reverts commit 5c03909a11.
2022-09-25 14:34:31 -05:00
eugenefischer
8ee1c5903e Merge branch 'master' into Dev_Vertex
# Conflicts:
#	src/main/java/GraphMLFileReader.java
#	src/main/java/InteractiveInterface.java
#	src/main/java/Simulator.java
2022-09-25 14:18:56 -05:00
eugenefischer
5c03909a11 Restore pre-filtering of singleton and saturating sequences 2022-09-22 01:39:13 -05:00
eugenefischer
e4e5a1f979 update version number 2022-09-22 00:00:02 -05:00
eugenefischer
73c83bf35d Add comment on map data encodng 2022-09-21 21:46:00 -05:00
eugenefischer
06e72314b0 Reword option menu item 2022-09-21 21:43:47 -05:00
eugenefischer
63317f2aa0 Reword output message 2022-09-21 18:08:52 -05:00
eugenefischer
a054c0c20a update TODO 2022-09-21 16:50:00 -05:00
eugenefischer
29b844afd2 by-hand merge of needed code from custom vertex branch 2022-09-21 16:48:26 -05:00
eugenefischer
dea4972927 remove prefiltering of singletons and saturating sequences 2022-09-21 16:09:08 -05:00
eugenefischer
9ae38bf247 Fix bug in correct match counter 2022-09-21 15:59:23 -05:00
eugenefischer
3ba305abdb Update ToDo 2022-09-21 13:30:30 -05:00
eugenefischer
3707923398 Merge remote-tracking branch 'origin/master' 2022-09-21 13:16:52 -05:00
eugenefischer
cf771ce574 parameterized sequence indices 2022-09-21 13:15:49 -05:00
f980722b56 update TODO 2022-09-21 18:09:37 +00:00
1df86f01df parameterized sequence indices 2022-03-05 12:03:31 -06:00
96ba57d653 Remove singleton sequences from wells in initial filtering 2022-03-04 16:14:17 -06:00
b602fb02f1 Remove obsolete comments 2022-03-02 23:35:24 -06:00
325e1ebe2b Add data on randomized well population behavior 2022-03-02 23:21:56 -06:00
df047267ee Add data on randomized well population behavior 2022-03-02 22:54:17 -06:00
03e8d31210 Add data on randomized well population behavior 2022-03-02 18:55:19 -06:00
582dc3ef40 Update readme 2022-03-02 12:39:40 -06:00
4c872ed48e Add optional stdout print flags 2022-03-01 15:27:04 -06:00
3fc39302c7 Add detail to error message 2022-03-01 15:24:14 -06:00
578bdc0fbf clarify help menu text 2022-03-01 15:08:43 -06:00
8275cf7740 Check for finite pairing error rate 2022-03-01 09:01:53 -06:00
64209691f0 Check for finite pairing error rate 2022-03-01 09:00:58 -06:00
1886800873 update readme 2022-03-01 08:54:32 -06:00
bedf0894bc update readme 2022-03-01 08:45:40 -06:00
2ac3451842 update readme 2022-03-01 08:43:48 -06:00
67ec3f3764 update readme 2022-03-01 08:43:18 -06:00
b5a8b7e2d5 update readme 2022-03-01 08:41:57 -06:00
9fb3095f0f Clarify help text 2022-03-01 08:40:34 -06:00
25acf920c2 Add version information 2022-03-01 08:34:35 -06:00
f301327693 Update readme with -graphml flag 2022-03-01 08:24:43 -06:00
e04d2d6777 Fix typos in help menu 2022-03-01 08:16:06 -06:00
3e41afaa64 bugfix 2022-02-27 19:08:29 -06:00
bc5d67680d Add flag to print metadata to stdout 2022-02-27 17:36:23 -06:00
f2347e8fc2 check verbose flag 2022-02-27 17:35:50 -06:00
c8364d8a6e check verbose flag 2022-02-27 17:34:20 -06:00
6f5afbc6ec Update readme with CLI arguments 2022-02-27 17:01:12 -06:00
fb4d22e7a4 Update readme with CLI arguments 2022-02-27 17:00:54 -06:00
e10350c214 Update readme with CLI arguments 2022-02-27 16:56:58 -06:00
b1155f8100 Format -help CLI option 2022-02-27 16:53:46 -06:00
12b003a69f Add -help CLI option 2022-02-27 16:45:30 -06:00
32c5bcaaff Deactivate file I/O announcement for CLI 2022-02-27 16:16:24 -06:00
2485ac4cf6 Add getters to MatchingResult 2022-02-27 16:15:26 -06:00
05556bce0c Add units to metadata 2022-02-27 16:08:59 -06:00
a822f69ea4 Control verbose output 2022-02-27 16:07:17 -06:00
3d1f8668ee Control verbose output 2022-02-27 16:03:57 -06:00
40c743308b Initialize wells 2022-02-27 15:54:47 -06:00
5246cc4a0c Re-implement command line options 2022-02-27 15:35:07 -06:00
a5f7c0641d Refactor for better encapsulation with CellSamples 2022-02-27 14:51:53 -06:00
8ebfc1469f Refactor plate to fill its own wells in its constructor 2022-02-27 14:25:53 -06:00
b53f5f1cc0 Refactor plate to fill its own wells in its constructor 2022-02-27 14:17:16 -06:00
974d2d650c Refactor plate to fill its own wells in its constructor 2022-02-27 14:17:11 -06:00
6b5837e6ce Add Vose's alias method to to-dos 2022-02-27 11:46:11 -06:00
b4cc240048 Update Readme 2022-02-26 11:03:31 -06:00
ff72c9b359 Update Readme 2022-02-26 11:02:23 -06:00
88eb8aca50 Update Readme 2022-02-26 11:01:44 -06:00
98bf452891 Update Readme 2022-02-26 11:01:20 -06:00
c2db4f87c1 Update Readme 2022-02-26 11:00:18 -06:00
8935407ade Get rid of GraphML reader, those files are larger than serialized files 2022-02-26 10:38:10 -06:00
9fcc20343d Fix GraphML writer 2022-02-26 10:36:00 -06:00
817fe51708 Code cleanup 2022-02-26 09:56:46 -06:00
1ea68045ce Refactor cdr3 matching to use new Vertex class 2022-02-26 09:49:16 -06:00
75b2aa9553 testing graph attributes 2022-02-26 08:58:52 -06:00
b3dc10f287 add graph attributes to graphml writer 2022-02-26 08:15:48 -06:00
fb8d8d8785 make heap type an enum 2022-02-26 08:15:31 -06:00
ab437512e9 make Vertex serializable 2022-02-26 07:45:36 -06:00
7b03a3cce8 bugfix 2022-02-26 07:35:34 -06:00
f032d3e852 rewrite GraphML importer/exporter 2022-02-26 07:34:07 -06:00
b604b1d3cd Changing graph to use Vertex class 2022-02-26 06:19:08 -06:00
e4d094d796 Adding GraphML output to options menu 2022-02-24 17:22:07 -06:00
f385ebc31f Update vertex class 2022-02-24 16:25:01 -06:00
8745550e11 add MWM algorithm type to matching metadata 2022-02-24 16:24:48 -06:00
41805135b3 remove unused import 2022-02-24 16:04:30 -06:00
373a5e02f9 Refactor to make CellSample class more self-contained 2022-02-24 16:03:49 -06:00
7f18311054 fix typos 2022-02-24 15:55:32 -06:00
bcb816c3e6 Reformat TODO 2022-02-24 15:48:10 -06:00
dad0fd35fd Update readme to reflect wells with random population implemented 2022-02-24 15:47:08 -06:00
35d580cfcf Update readme to reflect wells with random population implemented 2022-02-24 15:45:03 -06:00
ab8d98ed81 Update readme to reflect new default caching behavior. 2022-02-24 15:39:15 -06:00
3d9890e16a Change GraphModificationFunctions to only save edges if graph data is cached 2022-02-24 15:32:27 -06:00
dd64ac2731 Change GraphModificationFunctions to interface 2022-02-24 15:18:09 -06:00
a5238624f1 Change default graph caching behavior to false 2022-02-24 15:14:28 -06:00
d8ba42b801 Fix Algorithm Options menu output 2022-02-24 14:59:08 -06:00
8edd89d784 Added heap type selection, fixed error handling 2022-02-24 14:48:19 -06:00
2829b88689 Update readme to reflect caching changes 2022-02-24 12:47:26 -06:00
108b0ec13f Improve options menu wording 2022-02-24 12:42:09 -06:00
a8b58d3f79 Output new setting when changing options 2022-02-24 12:38:15 -06:00
bf64d57731 implement option menu for file caching 2022-02-24 12:30:47 -06:00
c068c3db3c implement option menu for file caching 2022-02-23 20:35:31 -06:00
4bcda9b66c update readme 2022-02-23 13:22:04 -06:00
17ae763c6c Generate populations correctly 2022-02-23 10:37:40 -06:00
decdb147a9 Cache everything 2022-02-23 10:30:42 -06:00
74ffbfd8ac make everything use same random number generator 2022-02-23 09:29:21 -06:00
08699ce8ce Change output order to match interactive UI 2022-02-23 08:56:09 -06:00
69b0cc535c Error checking 2022-02-23 08:55:07 -06:00
e58f7b0a55 checking for possible divide by zero error. 2022-02-23 08:54:14 -06:00
dd2164c250 implement sample plates with random well populations 2022-02-23 08:14:17 -06:00
7323093bdc change "getRandomNumber" to "getRandomInt" for consistency. 2022-02-23 08:13:52 -06:00
f904cf6672 add more data caching code 2022-02-23 08:13:06 -06:00
3ccee9891b change "concentrations" to "populations" for consistency 2022-02-23 08:12:48 -06:00
40c2be1cfb create populations string correctly 2022-02-23 08:11:01 -06:00
4b597c4e5e remove old testing code 2022-02-23 08:10:35 -06:00
b2398531a3 Update readme 2022-02-23 05:11:36 +00:00
23 changed files with 2025 additions and 853 deletions

223
readme.md
View File

@@ -12,7 +12,7 @@ Unlike pairSEQ, which calculates p-values for every TCR alpha/beta overlap and c
against a null distribution, BiGpairSEQ does not do any statistical calculations
directly.
BiGpairSEQ creates a [simple bipartite weighted graph](https://en.wikipedia.org/wiki/Bipartite_graph) representing the sample plate.
BiGpairSEQ creates a [weighted bipartite graph](https://en.wikipedia.org/wiki/Bipartite_graph) representing the sample plate.
The distinct TCRA and TCRB sequences form the two sets of vertices. Every TCRA/TCRB pair that share a well
are connected by an edge, with the edge weight set to the number of wells in which both sequences appear.
(Sequences present in *all* wells are filtered out prior to creating the graph, as there is no signal in their occupancy pattern.)
@@ -20,8 +20,8 @@ The problem of pairing TCRA/TCRB sequences thus reduces to the "assignment probl
matching on a bipartite graph--the subset of vertex-disjoint edges whose weights sum to the maximum possible value.
This is a well-studied combinatorial optimization problem, with many known solutions.
The most efficient algorithm known to the author for maximum weight matching of a bipartite graph with strictly integral weights
is from Duan and Su (2012). For a graph with m edges, n vertices per side, and maximum integer edge weight N,
The most efficient algorithm known to the author for maximum weight matching of a bipartite graph with strictly integral
weights is from Duan and Su (2012). For a graph with m edges, n vertices per side, and maximum integer edge weight N,
their algorithm runs in **O(m sqrt(n) log(N))** time. As the graph representation of a pairSEQ experiment is
bipartite with integer weights, this algorithm is ideal for BiGpairSEQ.
@@ -29,17 +29,13 @@ Unfortunately, it's a fairly new algorithm, and not yet implemented by the graph
So this program instead uses the Fibonacci heap-based algorithm of Fredman and Tarjan (1987), which has a worst-case
runtime of **O(n (n log(n) + m))**. The algorithm is implemented as described in Melhorn and Näher (1999).
The current version of the program uses a pairing heap instead of a Fibonacci heap for its priority queue,
which has lower theoretical efficiency but also lower complexity overhead, and is often equivalently performant
in practice.
## USAGE
### RUNNING THE PROGRAM
[Download the current version of BiGpairSEQ_Sim.](https://gitea.ejsf.synology.me/efischer/BiGpairSEQ/releases)
BiGpairSEQ_Sim is an executable .jar file. Requires Java 11 or higher. [OpenJDK 17](https://jdk.java.net/17/)
BiGpairSEQ_Sim is an executable .jar file. Requires Java 14 or higher. [OpenJDK 17](https://jdk.java.net/17/)
recommended.
Run with the command:
@@ -47,39 +43,75 @@ Run with the command:
`java -jar BiGpairSEQ_Sim.jar`
Processing sample plates with tens of thousands of sequences may require large amounts
of RAM. It is often desirable to increase the JVM maximum heap allocation with the -Xmx flag.
of RAM. It is often desirable to increase the JVM maximum heap allocation with the `-Xmx` flag.
For example, to run the program with 32 gigabytes of memory, use the command:
`java -Xmx32G -jar BiGpairSEQ_Sim.jar`
Once running, BiGpairSEQ_Sim has an interactive, menu-driven CLI for generating files and simulating TCR pairing. The
main menu looks like this:
There are a number of command line options, to allow the program to be used in shell scripts. For a full list,
use the `-help` flag:
`java -jar BiGpairSEQ_Sim.jar -help`
If no command line arguments are given, BiGpairSEQ_Sim will launch with an interactive, menu-driven CLI for
generating files and simulating TCR pairing. The main menu looks like this:
```
--------BiGPairSEQ SIMULATOR--------
ALPHA/BETA T CELL RECEPTOR MATCHING
USING WEIGHTED BIPARTITE GRAPHS
USING WEIGHTED BIPARTITE GRAPHS
------------------------------------
Please select an option:
1) Generate a population of distinct cells
2) Generate a sample plate of T cells
3) Generate CDR3 alpha/beta occupancy data and overlap graph
4) Simulate bipartite graph CDR3 alpha/beta matching (BiGpairSEQ)
8) Options
9) About/Acknowledgments
0) Exit
```
### OUTPUT
By default, the Options menu looks like this:
```
--------------OPTIONS---------------
1) Turn on cell sample file caching
2) Turn on plate file caching
3) Turn on graph/data file caching
4) Turn off serialized binary graph output
5) Turn on GraphML graph output
6) Maximum weight matching algorithm options
0) Return to main menu
```
### INPUT/OUTPUT
To run the simulation, the program reads and writes 4 kinds of files:
* Cell Sample files in CSV format
* Sample Plate files in CSV format
* Graph and Data files in binary object serialization format
* Graph/Data files in binary object serialization format
* Matching Results files in CSV format
When entering filenames, it is not necessary to include the file extension (.csv or .ser). When reading or
writing files, the program will automatically add the correct extension to any filename without one.
These files are often generated in sequence. When entering filenames, it is not necessary to include the file extension
(.csv or .ser). When reading or writing files, the program will automatically add the correct extension to any filename
without one.
To save file I/O time, the most recent instance of each of these four
files either generated or read from disk can be cached in program memory. When caching is active, subsequent uses of the
same data file won't need to be read in again until another file of that type is used or generated,
or caching is turned off for that file type. The program checks whether it needs to update its cached data by comparing
filenames as entered by the user. On encountering a new filename, the program flushes its cache and reads in the new file.
(Note that cached Graph/Data files must be transformed back into their original state after a matching experiment, which
may take some time. Whether file I/O or graph transformation takes longer for graph/data files is likely to be
device-specific.)
The program's caching behavior can be controlled in the Options menu. By default, all caching is OFF.
The program can optionally output Graph/Data files in GraphML format (.graphml) for data portability. This can be
turned on in the Options menu. By default, GraphML output is OFF.
---
#### Cell Sample Files
Cell Sample files consist of any number of distinct "T cells." Every cell contains
four sequences: Alpha CDR3, Beta CDR3, Alpha CDR1, Beta CDR1. The sequences are represented by
@@ -97,7 +129,6 @@ Comments are preceded by `#`
Structure:
---
# Sample contains 1 unique CDR1 for every 4 unique CDR3s.
| Alpha CDR3 | Beta CDR3 | Alpha CDR1 | Beta CDR1 |
|---|---|---|---|
@@ -121,15 +152,18 @@ Options when making a Sample Plate file:
* Standard deviation size
* Exponential
* Lambda value
* (Based on the slope of the graph in Figure 4C of the pairSEQ paper, the distribution of the original experiment was exponential with a lambda of approximately 0.6. (Howie, et al. 2015))
* *(Based on the slope of the graph in Figure 4C of the pairSEQ paper, the distribution of the original experiment was approximately exponential with a lambda ~0.6. (Howie, et al. 2015))*
* Total number of wells on the plate
* Number of sections on plate
* Number of T cells per well
* per section, if more than one section
* Well populations random or fixed
* If random, minimum and maximum population sizes
* If fixed
* Number of sections on plate
* Number of T cells per well
* per section, if more than one section
* Dropout rate
Files are in CSV format. There are no header labels. Every row represents a well.
Every column represents an individual cell, containing four sequences, depicted as an array string:
Every value represents an individual cell, containing four sequences, depicted as an array string:
`[CDR3A, CDR3B, CDR1A, CDR1B]`. So a representative cell might look like this:
`[525902, 791533, -1, 866282]`
@@ -139,7 +173,6 @@ Dropout sequences are replaced with the value `-1`. Comments are preceded by `#`
Structure:
---
```
# Cell source file name:
# Each row represents one well on the plate
@@ -155,8 +188,8 @@ Structure:
---
#### Graph and Data Files
Graph and Data files are serialized binaries of a Java object containing the weigthed bipartite graph representation of a
#### Graph/Data Files
Graph/Data files are serialized binaries of a Java object containing the weigthed bipartite graph representation of a
Sample Plate, along with the necessary metadata for matching and results output. Making them requires a Cell Sample file
(to construct a list of correct sequence pairs for checking the accuracy of BiGpairSEQ simulations) and a
Sample Plate file (to construct the associated occupancy graph).
@@ -164,22 +197,32 @@ Sample Plate file (to construct the associated occupancy graph).
These files can be several gigabytes in size. Writing them to a file lets us generate a graph and its metadata once,
then use it for multiple different BiGpairSEQ simulations.
Options for creating a Graph and Data file:
Options for creating a Graph/Data file:
* The Cell Sample file to use
* The Sample Plate file to use. (This must have been generated from the selected Cell Sample file.)
* Whether to simulate sequence read depth. If simulated:
* The read depth (number of times each sequence is read)
* The read error rate (probability a sequence is misread)
* The error collision rate (probability two misreads produce the same spurious sequence)
These files do not have a human-readable structure, and are not portable to other programs. (Export of graphs in a
portable data format may be implemented in the future. The tricky part is encoding the necessary metadata.)
These files do not have a human-readable structure, and are not portable to other programs.
*Optional GraphML output*
For portability of graph data to other software, turn on [GraphML](http://graphml.graphdrawing.org/index.html) output
in the Options menu in interactive mode, or use the `-graphml`command line argument. This will produce a .graphml file
for the weighted graph, with vertex attributes for sequence, type, and occupancy data. This graph contains all the data
necessary for the BiGpairSEQ matching algorithm. It does not include the data to measure pairing accuracy; for that,
compare the matching results to the original Cell Sample .csv file.
---
#### Matching Results Files
Matching results files consist of the results of a BiGpairSEQ matching simulation. Making them requires a Graph and
Data file. To save file I/O time, the data from the most recent Graph and Data file read or generated is cached
by the simulator. Subsequent BiGpairSEQ simulations run with the same input filename will use the cached version
rather than reading in again from disk.
Matching results files consist of the results of a BiGpairSEQ matching simulation. Making them requires a serialized
binary Graph/Data file (.ser). (Because .graphML files are larger than .ser files, BiGpairSEQ_Sim supports .graphML
output only. Graph/data input must use a serialized binary.)
Files are in CSV format. Rows are sequence pairings with extra relevant data. Columns are pairing-specific details.
Matching results files are in CSV format. Rows are sequence pairings with extra relevant data. Columns are pairing-specific details.
Metadata about the matching simulation is included as comments. Comments are preceded by `#`.
Options when running a BiGpairSEQ simulation of CDR3 alpha/beta matching:
@@ -194,7 +237,6 @@ Options when running a BiGpairSEQ simulation of CDR3 alpha/beta matching:
Example output:
---
```
# Source Sample Plate file: 4MilCellsPlate.csv
# Source Graph and Data file: 4MilCellsPlateGraph.ser
@@ -226,46 +268,117 @@ Example output:
P-values are calculated *after* BiGpairSEQ matching is completed, for purposes of comparison only,
using the (2021 corrected) formula from the original pairSEQ paper. (Howie, et al. 2015)
### PERFORMANCE
Performance details of the example excerpted above:
## PERFORMANCE (old results; need updating to reflect current, improved simulator performance)
On a home computer with a Ryzen 5600X CPU, 64GB of 3200MHz DDR4 RAM (half of which was allocated to the Java Virtual Machine), and a PCIe 3.0 SSD, running Linux Mint 20.3 Edge (5.13 kernel),
the author ran a BiGpairSEQ simulation of a 96-well sample plate with 30,000 T cells/well comprising ~11,800 alphas and betas,
taken from a sample of 4,000,000 distinct cells with an exponential frequency distribution.
taken from a sample of 4,000,000 distinct cells with an exponential frequency distribution (lambda 0.6).
With min/max occupancy threshold of 3 and 94 wells for matching, and no other pre-filtering, BiGpairSEQ identified 5,151
correct pairings and 18 incorrect pairings, for an accuracy of 99.652%.
The simulation time was 14'22". If intermediate results were held in memory, this would be equivalent to the total elapsed time.
The total simulation time was 14'22". If intermediate results were held in memory, this would be equivalent to the total elapsed time.
Since this implementation of BiGpairSEQ writes intermediate results to disk (to improve the efficiency of *repeated* simulations
with different filtering options), the actual elapsed time was greater. File I/O time was not measured, but took
slightly less time than the simulation itself. Real elapsed time from start to finish was under 30 minutes.
As mentioned in the theory section, performance could be improved by implementing a more efficient algorithm for finding
the maximum weight matching.
## BEHAVIOR WITH RANDOMIZED WELL POPULATIONS
A series of BiGpairSEQ simulations were conducted using a cell sample file of 3.5 million unique T cells. From these cells,
10 sample plate files were created. All of these sample plates had 96 wells, used an exponential distribution with a lambda of 0.6, and
had a sequence dropout rate of 10%.
The well populations of the plates were:
* One sample plate with 1000 T cells/well
* One sample plate with 2000 T cells/well
* One sample plate with 3000 T cells/well
* One sample plate with 4000 T cells/well
* One sample plate with 5000 T cells/well
* Five sample plates with each individual well's population randomized, from 1000 to 5000 T cells. (Average population ~3000 T cells/well.)
All BiGpairSEQ simulations were run with a low overlap threshold of 3 and a high overlap threshold of 94.
No optional filters were used, so pairing was attempted for all sequences with overlaps within the threshold values.
Constant well population plate results:
| |1000 Cell/Well Plate|2000 Cell/Well Plate|3000 Cell/Well Plate|4000 Cell/Well Plate|5000 Cell/Well Plate
|---|---|---|---|---|---|
|Total Alphas Found|6407|7330|7936|8278|8553|
|Total Betas Found|6405|7333|7968|8269|8582|
|Pairing Attempt Rate|0.661|0.653|0.600|0.579|0.559|
|Correct Pairing Count|4231|4749|4723|4761|4750|
|Incorrect Pairing Count|3|34|40|26|29|
|Pairing Error Rate|0.000709|0.00711|0.00840|0.00543|0.00607|
|Simulation Time (Seconds)|500|643|700|589|598|
Randomized well population plate results:
| |Random Plate 1 | Random Plate 2|Random Plate 3|Random Plate 4|Random Plate 5|Average|
|---|---|---|---|---|---|---|
Total Alphas Found|7853|7904|7964|7898|7917|7907|
Total Betas Found|7851|7891|7920|7910|7894|7893|
Pairing Attempt Rate|0.607|0.610|0.601|0.605|0.603|0.605|
Correct Pairing Count|4718|4782|4721|4755|4731|4741|
Incorrect Pairing Count|51|35|42|27|29|37|
Pairing Error Rate|0.0107|0.00727|0.00882|0.00565|0.00609|0.00771|
Simulation Time (Seconds)|590|677|730|618|615|646|
The average results for the randomized plates are closest to the constant plate with 3000 T cells/well.
This and several other tests indicate that BiGpairSEQ treats a sample plate with a highly variable number of T cells/well
roughly as though it had a constant well population equal to the plate's average well population.
## TODO
* ~~Try invoking GC at end of workloads to reduce paging to disk~~ DONE
* Hold graph data in memory until another graph is read-in? ~~ABANDONED~~ ~~UNABANDONED~~ DONE
* ~~Hold graph data in memory until another graph is read-in? ABANDONED UNABANDONED~~ DONE
* ~~*No, this won't work, because BiGpairSEQ simulations alter the underlying graph based on filtering constraints. Changes would cascade with multiple experiments.*~~
* Might have figured out a way to do it, by taking edges out and then putting them back into the graph. This may actually be possible. If so, awesome.
* See if there's a reasonable way to reformat Sample Plate files so that wells are columns instead of rows.
* Might have figured out a way to do it, by taking edges out and then putting them back into the graph. This may actually be possible.
* It is possible, though the modifications to the graph incur their own performance penalties. Need testing to see which option is best. It may be computer-specific.
* ~~Test whether pairing heap (currently used) or Fibonacci heap is more efficient for priority queue in current matching algorithm~~ DONE
* ~~in theory Fibonacci heap should be more efficient, but complexity overhead may eliminate theoretical advantage~~
* ~~Add controllable heap-type parameter?~~
* Parameter implemented. Fibonacci heap the current default.
* ~~Implement sample plates with random numbers of T cells per well.~~ DONE
* Possible BiGpairSEQ advantage over pairSEQ: BiGpairSEQ is resilient to variations in well population sizes on a sample plate; pairSEQ is not due to nature of probability calculations.
* preliminary data suggests that BiGpairSEQ behaves roughly as though the whole plate had whatever the *average* well concentration is, but that's still speculative.
* ~~See if there's a reasonable way to reformat Sample Plate files so that wells are columns instead of rows.~~
* ~~Problem is variable number of cells in a well~~
* ~~Apache Commons CSV library writes entries a row at a time~~
* _Got this working, but at the cost of a profoundly strange bug in graph occupancy filtering. Have reverted the repo until I can figure out what caused that. Given how easily Thingiverse transposes CSV matrices in R, might not even be worth fixing._
* Re-implement command line arguments, to enable scripting and statistical simulation studies
* Implement sample plates with random numbers of T cells per well.
* Possible BiGpairSEQ advantage over pairSEQ: BiGpairSEQ is resilient to variations in well population sizes on a sample plate; pairSEQ is not.
* preliminary data suggests that BiGpairSEQ behaves roughly as though the whole plate had whatever the *average* well concentration is, but that's still speculative.
* Enable GraphML output in addition to serialized object binaries, for data portability
* Custom vertex type with attribute for sequence occupancy?
* Got this working, but at the cost of a profoundly strange bug in graph occupancy filtering. Have reverted the repo until I can figure out what caused that. Given how easily Thingiverse transposes CSV matrices in R, might not even be worth fixing.
* ~~Enable GraphML output in addition to serialized object binaries, for data portability~~ DONE
* ~~Have a branch where this is implemented, but there's a bug that broke matching. Don't currently have time to fix.~~
* ~~Re-implement command line arguments, to enable scripting and statistical simulation studies~~ DONE
* ~~Implement custom Vertex class to simplify code and make it easier to implement different MWM algorithms~~ DONE
* Advantage: would eliminate the need to use maps to associate vertices with sequences, which would make the code easier to understand.
* This also seems to be faster when using the same algorithm than the version with lots of maps, which is a nice bonus!
* ~~Implement simulation of read depth, and of read errors. Pre-filter graph for difference in read count to eliminate spurious sequences.~~ DONE
* Pre-filtering based on comparing (read depth) * (occupancy) to (read count) for each sequence works extremely well
* ~~Add read depth simulation options to CLI~~ DONE
* ~~Update graphml output to reflect current Vertex class attributes~~ DONE
* Individual well data from the SequenceRecords could be included, if there's ever a reason for it
* Update matching metadata output options in CLI
* Update performance data in this readme
* Re-implement CDR1 matching method
* Refactor simulator code to collect all needed data in a single scan of the plate
* Currently it scans once for the vertices and then again for the edge weights. This made simulating read depth awkward, and incompatible with caching of plate files.
* This would be a fairly major rewrite of the simulator code, but could make things faster, and would definitely make them cleaner.
* Implement Duan and Su's maximum weight matching algorithm
* Add controllable algorithm-type parameter?
* Test whether pairing heap (currently used) or Fibonacci heap is more efficient for priority queue in current matching algorithm
* in theory Fibonacci heap should be more efficient, but complexity overhead may eliminate theoretical advantage
* Add controllable heap-type parameter?
* Add controllable algorithm-type parameter?
* This would be fun and valuable, but probably take more time than I have for a hobby project.
* Implement an auction algorithm for maximum weight matching
* Implement an algorithm for approximating a maximum weight matching
* Some of these run in linear or near-linear time
* given that the underlying biological samples have many, many sources of error, this would probably be the most useful option in practice. It seems less mathematically elegant, though, and so less fun for me.
* Implement Vose's alias method for arbitrary statistical distributions of cells
* Should probably refactor to use apache commons rng for this
* Use commons JCS for caching
* Parameterize pre-filtering. Currently, sequences present in all wells are filtered out before constructing the graph, which massively reduces graph size. But, ideally, no pre-filtering would be necessary.
## CITATIONS
* Howie, B., Sherwood, A. M., et al. ["High-throughput pairing of T cell receptor alpha and beta sequences."](https://pubmed.ncbi.nlm.nih.gov/26290413/) Sci. Transl. Med. 7, 301ra131 (2015)
@@ -277,7 +390,7 @@ slightly less time than the simulation itself. Real elapsed time from start to f
* [JGraphT](https://jgrapht.org) -- Graph theory data structures and algorithms
* [JHeaps](https://www.jheaps.org) -- For pairing heap priority queue used in maximum weight matching algorithm
* [Apache Commons CSV](https://commons.apache.org/proper/commons-csv/) -- For CSV file output
* [Apache Commons CLI](https://commons.apache.org/proper/commons-cli/) -- To enable command line arguments for scripting. (**Awaiting re-implementation**.)
* [Apache Commons CLI](https://commons.apache.org/proper/commons-cli/) -- To enable command line arguments for scripting.
## ACKNOWLEDGEMENTS
BiGpairSEQ was conceived in collaboration with Dr. Alice MacQueen, who brought the original

View File

@@ -1,8 +1,22 @@
//main class. Only job is to choose which interface to use, and hold graph data in memory
import java.util.Random;
//main class. For choosing interface type and holding settings
public class BiGpairSEQ {
private static final Random rand = new Random();
private static CellSample cellSampleInMemory = null;
private static String cellFilename = null;
private static Plate plateInMemory = null;
private static String plateFilename = null;
private static GraphWithMapData graphInMemory = null;
private static String graphFilename = null;
private static boolean cacheCells = false;
private static boolean cachePlate = false;
private static boolean cacheGraph = false;
private static HeapType priorityQueueHeapType = HeapType.FIBONACCI;
private static boolean outputBinary = true;
private static boolean outputGraphML = false;
private static final String version = "version 3.0";
public static void main(String[] args) {
if (args.length == 0) {
@@ -10,33 +24,154 @@ public class BiGpairSEQ {
}
else {
//This will be uncommented when command line arguments are re-implemented.
//CommandLineInterface.startCLI(args);
System.out.println("Command line arguments are still being re-implemented.");
CommandLineInterface.startCLI(args);
//System.out.println("Command line arguments are still being re-implemented.");
}
}
public static GraphWithMapData getGraph() {
return graphInMemory;
public static Random getRand() {
return rand;
}
public static void setGraph(GraphWithMapData g) {
public static CellSample getCellSampleInMemory() {
return cellSampleInMemory;
}
public static void setCellSampleInMemory(CellSample cellSample, String filename) {
if(cellSampleInMemory != null) {
clearCellSampleInMemory();
}
cellSampleInMemory = cellSample;
cellFilename = filename;
System.out.println("Cell sample file " + filename + " cached.");
}
public static void clearCellSampleInMemory() {
cellSampleInMemory = null;
cellFilename = null;
System.gc();
System.out.println("Cell sample file cache cleared.");
}
public static String getCellFilename() {
return cellFilename;
}
public static Plate getPlateInMemory() {
return plateInMemory;
}
public static void setPlateInMemory(Plate plate, String filename) {
if(plateInMemory != null) {
clearPlateInMemory();
}
plateInMemory = plate;
plateFilename = filename;
System.out.println("Sample plate file " + filename + " cached.");
}
public static void clearPlateInMemory() {
plateInMemory = null;
plateFilename = null;
System.gc();
System.out.println("Sample plate file cache cleared.");
}
public static String getPlateFilename() {
return plateFilename;
}
public static GraphWithMapData getGraphInMemory() {return graphInMemory;
}
public static void setGraphInMemory(GraphWithMapData g, String filename) {
if (graphInMemory != null) {
clearGraph();
clearGraphInMemory();
}
graphInMemory = g;
graphFilename = filename;
System.out.println("Graph and data file " + filename + " cached.");
}
public static void clearGraph() {
public static void clearGraphInMemory() {
graphInMemory = null;
graphFilename = null;
System.gc();
System.out.println("Graph and data file cache cleared.");
}
public static String getGraphFilename() {
return graphFilename;
}
public static void setGraphFilename(String filename) {
graphFilename = filename;
public static boolean cacheCells() {
return cacheCells;
}
public static void setCacheCells(boolean cacheCells) {
//if not caching, clear the memory
if(!cacheCells){
BiGpairSEQ.clearCellSampleInMemory();
System.out.println("Cell sample file caching: OFF.");
}
else {
System.out.println("Cell sample file caching: ON.");
}
BiGpairSEQ.cacheCells = cacheCells;
}
public static boolean cachePlate() {
return cachePlate;
}
public static void setCachePlate(boolean cachePlate) {
//if not caching, clear the memory
if(!cachePlate) {
BiGpairSEQ.clearPlateInMemory();
System.out.println("Sample plate file caching: OFF.");
}
else {
System.out.println("Sample plate file caching: ON.");
}
BiGpairSEQ.cachePlate = cachePlate;
}
public static boolean cacheGraph() {
return cacheGraph;
}
public static void setCacheGraph(boolean cacheGraph) {
//if not caching, clear the memory
if(!cacheGraph) {
BiGpairSEQ.clearGraphInMemory();
System.out.println("Graph/data file caching: OFF.");
}
else {
System.out.println("Graph/data file caching: ON.");
}
BiGpairSEQ.cacheGraph = cacheGraph;
}
public static String getPriorityQueueHeapType() {
return priorityQueueHeapType.name();
}
public static void setPairingHeap() {
priorityQueueHeapType = HeapType.PAIRING;
}
public static void setFibonacciHeap() {
priorityQueueHeapType = HeapType.FIBONACCI;
}
public static boolean outputBinary() {return outputBinary;}
public static void setOutputBinary(boolean b) {outputBinary = b;}
public static boolean outputGraphML() {return outputGraphML;}
public static void setOutputGraphML(boolean b) {outputGraphML = b;}
public static String getVersion() { return version; }
}

View File

@@ -12,7 +12,8 @@ import java.util.List;
public class CellFileReader {
private String filename;
private List<Integer[]> distinctCells = new ArrayList<>();
private List<String[]> distinctCells = new ArrayList<>();
private Integer cdr1Freq;
public CellFileReader(String filename) {
if(!filename.matches(".*\\.csv")){
@@ -31,26 +32,34 @@ public class CellFileReader {
CSVParser parser = new CSVParser(reader, cellFileFormat);
){
for(CSVRecord record: parser.getRecords()) {
Integer[] cell = new Integer[4];
cell[0] = Integer.valueOf(record.get("Alpha CDR3"));
cell[1] = Integer.valueOf(record.get("Beta CDR3"));
cell[2] = Integer.valueOf(record.get("Alpha CDR1"));
cell[3] = Integer.valueOf(record.get("Beta CDR1"));
String[] cell = new String[4];
cell[0] = record.get("Alpha CDR3");
cell[1] = record.get("Beta CDR3");
cell[2] = record.get("Alpha CDR1");
cell[3] = record.get("Beta CDR1");
distinctCells.add(cell);
}
} catch(IOException ex){
System.out.println("cell file " + filename + " not found.");
System.err.println(ex);
}
//get CDR1 frequency
ArrayList<String> cdr1Alphas = new ArrayList<>();
for (String[] cell : distinctCells) {
cdr1Alphas.add(cell[3]);
}
double count = cdr1Alphas.stream().distinct().count();
count = Math.ceil(distinctCells.size() / count);
cdr1Freq = (int) count;
}
public CellSample getCellSample() {
return new CellSample(distinctCells, cdr1Freq);
}
public String getFilename() { return filename;}
public List<Integer[]> getCells(){
return distinctCells;
}
public Integer getCellCount() {
return distinctCells.size();
}
}

View File

@@ -11,7 +11,7 @@ import java.util.List;
public class CellFileWriter {
private String[] headers = {"Alpha CDR3", "Beta CDR3", "Alpha CDR1", "Beta CDR1"};
List<Integer[]> cells;
List<String[]> cells;
String filename;
Integer cdr1Freq;
@@ -35,7 +35,7 @@ public class CellFileWriter {
printer.printComment("Sample contains 1 unique CDR1 for every " + cdr1Freq + "unique CDR3s.");
printer.printRecords(cells);
} catch(IOException ex){
System.out.println("Could not make new file named "+filename);
System.out.println("Could not make new file named " + filename);
System.err.println(ex);
}
}

View File

@@ -1,16 +1,51 @@
import java.util.ArrayList;
import java.util.Collections;
import java.util.List;
import java.util.stream.IntStream;
public class CellSample {
private List<Integer[]> cells;
private List<String[]> cells;
private Integer cdr1Freq;
public CellSample(List<Integer[]> cells, Integer cdr1Freq){
public CellSample(Integer numDistinctCells, Integer cdr1Freq){
this.cdr1Freq = cdr1Freq;
List<Integer> numbersCDR3 = new ArrayList<>();
List<Integer> numbersCDR1 = new ArrayList<>();
Integer numDistCDR3s = 2 * numDistinctCells + 1;
//Assign consecutive integers for each CDR3. This ensures they are all unique.
IntStream.range(1, numDistCDR3s + 1).forEach(i -> numbersCDR3.add(i));
//After all CDR3s are assigned, start assigning consecutive integers to CDR1s
//There will usually be fewer integers in the CDR1 list, which will allow repeats below
IntStream.range(numDistCDR3s + 1, numDistCDR3s + 1 + (numDistCDR3s / cdr1Freq) + 1).forEach(i -> numbersCDR1.add(i));
//randomize the order of the numbers in the lists
Collections.shuffle(numbersCDR3);
Collections.shuffle(numbersCDR1);
//Each cell represented by 4 values
//two CDR3s, and two CDR1s. First two values are CDR3s (alpha, beta), second two are CDR1s (alpha, beta)
List<String[]> distinctCells = new ArrayList<>();
for(int i = 0; i < numbersCDR3.size() - 1; i = i + 2){
//Go through entire CDR3 list once, make pairs of alphas and betas
String tmpCDR3a = numbersCDR3.get(i).toString();
String tmpCDR3b = numbersCDR3.get(i+1).toString();
//Go through the (likely shorter) CDR1 list as many times as necessary, make pairs of alphas and betas
String tmpCDR1a = numbersCDR1.get(i % numbersCDR1.size()).toString();
String tmpCDR1b = numbersCDR1.get((i+1) % numbersCDR1.size()).toString();
//Make the array representing the cell
String[] tmp = {tmpCDR3a, tmpCDR3b, tmpCDR1a, tmpCDR1b};
//Add the cell to the list of distinct cells
distinctCells.add(tmp);
}
this.cells = distinctCells;
}
public CellSample(List<String[]> cells, Integer cdr1Freq){
this.cells = cells;
this.cdr1Freq = cdr1Freq;
}
public List<Integer[]> getCells(){
public List<String[]> getCells(){
return cells;
}
@@ -18,7 +53,7 @@ public class CellSample {
return cdr1Freq;
}
public Integer population(){
public Integer getCellCount(){
return cells.size();
}

View File

@@ -1,5 +1,9 @@
import org.apache.commons.cli.*;
import java.io.IOException;
import java.util.Arrays;
import java.util.stream.Stream;
/*
* Class for parsing options passed to program from command line
*
@@ -29,6 +33,12 @@ import org.apache.commons.cli.*;
* cellfile : name of the cell sample file to use as input
* platefile : name of the sample plate file to use as input
* output : name of the output file
* graphml : output a graphml file
* binary : output a serialized binary object file
* IF SIMULATING READ DEPTH, ALL THESE ARE REQUIRED. Absence indicates not simulating read depth
* readdepth: number of reads per sequence
* readerrorprob: probability of reading a sequence incorrectly
* errcollisionprob: probability of two read errors being identical
*
* Match flags:
* graphFile : name of graph and data file to use as input
@@ -43,242 +53,185 @@ import org.apache.commons.cli.*;
public class CommandLineInterface {
public static void startCLI(String[] args) {
//These command line options are a big mess
//Really, I don't think command line tools are expected to work in this many different modes
//making cells, making plates, and matching are the sort of thing that UNIX philosophy would say
//should be three separate programs.
//There might be a way to do it with option parameters?
//main options set
Options mainOptions = new Options();
Option makeCells = Option.builder("cells")
.longOpt("make-cells")
.desc("Makes a file of distinct cells")
.build();
Option makePlate = Option.builder("plates")
.longOpt("make-plates")
.desc("Makes a sample plate file")
.build();
Option makeGraph = Option.builder("graph")
.longOpt("make-graph")
.desc("Makes a graph and data file")
.build();
Option matchCDR3 = Option.builder("match")
.longOpt("match-cdr3")
.desc("Match CDR3s. Requires a cell sample file and any number of plate files.")
.build();
OptionGroup mainGroup = new OptionGroup();
mainGroup.addOption(makeCells);
mainGroup.addOption(makePlate);
mainGroup.addOption(makeGraph);
mainGroup.addOption(matchCDR3);
mainGroup.setRequired(true);
mainOptions.addOptionGroup(mainGroup);
//Reuse clones of this for other options groups, rather than making it lots of times
Option outputFile = Option.builder("o")
.longOpt("output-file")
.hasArg()
.argName("filename")
.desc("Name of output file")
.build();
mainOptions.addOption(outputFile);
//Options cellOptions = new Options();
Option numCells = Option.builder("nc")
.longOpt("num-cells")
.desc("The number of distinct cells to generate")
.hasArg()
.argName("number")
.build();
mainOptions.addOption(numCells);
Option cdr1Freq = Option.builder("d")
.longOpt("peptide-diversity-factor")
.hasArg()
.argName("number")
.desc("Number of distinct CDR3s for every CDR1")
.build();
mainOptions.addOption(cdr1Freq);
//Option cellOutput = (Option) outputFile.clone();
//cellOutput.setRequired(true);
//mainOptions.addOption(cellOutput);
//Options plateOptions = new Options();
Option inputCells = Option.builder("c")
.longOpt("cell-file")
.hasArg()
.argName("file")
.desc("The cell sample file used for filling wells")
.build();
mainOptions.addOption(inputCells);
Option numWells = Option.builder("w")
.longOpt("num-wells")
.hasArg()
.argName("number")
.desc("The number of wells on each plate")
.build();
mainOptions.addOption(numWells);
Option numPlates = Option.builder("np")
.longOpt("num-plates")
.hasArg()
.argName("number")
.desc("The number of plate files to output")
.build();
mainOptions.addOption(numPlates);
//Option plateOutput = (Option) outputFile.clone();
//plateOutput.setRequired(true);
//plateOutput.setDescription("Prefix for plate output filenames");
//mainOptions.addOption(plateOutput);
Option plateErr = Option.builder("err")
.longOpt("drop-out-rate")
.hasArg()
.argName("number")
.desc("Well drop-out rate. (Probability between 0 and 1)")
.build();
mainOptions.addOption(plateErr);
Option plateConcentrations = Option.builder("t")
.longOpt("t-cells-per-well")
.hasArgs()
.argName("number 1, number 2, ...")
.desc("Number of T cells per well for each plate section")
.build();
mainOptions.addOption(plateConcentrations);
//different distributions, mutually exclusive
OptionGroup plateDistributions = new OptionGroup();
Option plateExp = Option.builder("exponential")
.desc("Sample from distinct cells with exponential frequency distribution")
.build();
plateDistributions.addOption(plateExp);
Option plateGaussian = Option.builder("gaussian")
.desc("Sample from distinct cells with gaussain frequency distribution")
.build();
plateDistributions.addOption(plateGaussian);
Option platePoisson = Option.builder("poisson")
.desc("Sample from distinct cells with poisson frequency distribution")
.build();
plateDistributions.addOption(platePoisson);
mainOptions.addOptionGroup(plateDistributions);
Option plateStdDev = Option.builder("stddev")
.desc("Standard deviation for gaussian distribution")
.hasArg()
.argName("number")
.build();
mainOptions.addOption(plateStdDev);
Option plateLambda = Option.builder("lambda")
.desc("Lambda for exponential distribution")
.hasArg()
.argName("number")
.build();
mainOptions.addOption(plateLambda);
//
// String cellFile, String filename, Double stdDev,
// Integer numWells, Integer numSections,
// Integer[] concentrations, Double dropOutRate
//
//Options matchOptions = new Options();
inputCells.setDescription("The cell sample file to be used for matching.");
mainOptions.addOption(inputCells);
Option lowThresh = Option.builder("low")
.longOpt("low-threshold")
.hasArg()
.argName("number")
.desc("Sets the minimum occupancy overlap to attempt matching")
.build();
mainOptions.addOption(lowThresh);
Option highThresh = Option.builder("high")
.longOpt("high-threshold")
.hasArg()
.argName("number")
.desc("Sets the maximum occupancy overlap to attempt matching")
.build();
mainOptions.addOption(highThresh);
Option occDiff = Option.builder("occdiff")
.longOpt("occupancy-difference")
.hasArg()
.argName("Number")
.desc("Maximum difference in alpha/beta occupancy to attempt matching")
.build();
mainOptions.addOption(occDiff);
Option overlapPer = Option.builder("ovper")
.longOpt("overlap-percent")
.hasArg()
.argName("Percent")
.desc("Minimum overlap percent to attempt matching (0 -100)")
.build();
mainOptions.addOption(overlapPer);
Option inputPlates = Option.builder("p")
.longOpt("plate-files")
.hasArgs()
.desc("Plate files to match")
.build();
mainOptions.addOption(inputPlates);
//Options sets for the different modes
Options mainOptions = buildMainOptions();
Options cellOptions = buildCellOptions();
Options plateOptions = buildPlateOptions();
Options graphOptions = buildGraphOptions();
Options matchOptions = buildMatchCDR3options();
CommandLineParser parser = new DefaultParser();
try {
CommandLine line = parser.parse(mainOptions, args);
if(line.hasOption("match")){
//line = parser.parse(mainOptions, args);
//String cellFile = line.getOptionValue("c");
String graphFile = line.getOptionValue("g");
Integer lowThreshold = Integer.valueOf(line.getOptionValue(lowThresh));
Integer highThreshold = Integer.valueOf(line.getOptionValue(highThresh));
Integer occupancyDifference = Integer.valueOf(line.getOptionValue(occDiff));
Integer overlapPercent = Integer.valueOf(line.getOptionValue(overlapPer));
for(String plate: line.getOptionValues("p")) {
matchCDR3s(graphFile, lowThreshold, highThreshold, occupancyDifference, overlapPercent);
}
try{
CommandLine line = parser.parse(mainOptions, Arrays.copyOfRange(args, 0, 1));
if (line.hasOption("help")) {
HelpFormatter formatter = new HelpFormatter();
formatter.printHelp("BiGpairSEQ_Sim.jar", mainOptions);
System.out.println();
formatter.printHelp("BiGpairSEQ_Sim.jar -cells", cellOptions);
System.out.println();
formatter.printHelp("BiGpairSEQ_Sim.jar -plate", plateOptions);
System.out.println();
formatter.printHelp("BiGpairSEQ_Sim.jar -graph", graphOptions);
System.out.println();
formatter.printHelp("BiGpairSEQ_Sim.jar -match", matchOptions);
}
else if(line.hasOption("cells")){
//line = parser.parse(mainOptions, args);
else if (line.hasOption("version")) {
System.out.println("BiGpairSEQ_Sim " + BiGpairSEQ.getVersion());
}
else if (line.hasOption("cells")) {
line = parser.parse(cellOptions, Arrays.copyOfRange(args, 1, args.length));
Integer number = Integer.valueOf(line.getOptionValue("n"));
Integer diversity = Integer.valueOf(line.getOptionValue("d"));
String filename = line.getOptionValue("o");
Integer numDistCells = Integer.valueOf(line.getOptionValue("nc"));
Integer freq = Integer.valueOf(line.getOptionValue("d"));
makeCells(filename, numDistCells, freq);
makeCells(filename, number, diversity);
}
else if(line.hasOption("plates")){
//line = parser.parse(mainOptions, args);
String cellFile = line.getOptionValue("c");
String filenamePrefix = line.getOptionValue("o");
Integer numWellsOnPlate = Integer.valueOf(line.getOptionValue("w"));
Integer numPlatesToMake = Integer.valueOf(line.getOptionValue("np"));
String[] concentrationsToUseString = line.getOptionValues("t");
Integer numSections = concentrationsToUseString.length;
Integer[] concentrationsToUse = new Integer[numSections];
for(int i = 0; i <numSections; i++){
concentrationsToUse[i] = Integer.valueOf(concentrationsToUseString[i]);
else if (line.hasOption("plate")) {
line = parser.parse(plateOptions, Arrays.copyOfRange(args, 1, args.length));
//get the cells
String cellFilename = line.getOptionValue("c");
CellSample cells = getCells(cellFilename);
//get the rest of the parameters
Integer[] populations;
String outputFilename = line.getOptionValue("o");
Integer numWells = Integer.parseInt(line.getOptionValue("w"));
Double dropoutRate = Double.parseDouble(line.getOptionValue("err"));
if (line.hasOption("random")) {
//Array holding values of minimum and maximum populations
Integer[] min_max = Stream.of(line.getOptionValues("random"))
.mapToInt(Integer::parseInt)
.boxed()
.toArray(Integer[]::new);
populations = BiGpairSEQ.getRand().ints(min_max[0], min_max[1] + 1)
.limit(numWells)
.boxed()
.toArray(Integer[]::new);
}
Double dropOutRate = Double.valueOf(line.getOptionValue("err"));
if(line.hasOption("exponential")){
Double lambda = Double.valueOf(line.getOptionValue("lambda"));
for(int i = 1; i <= numPlatesToMake; i++){
makePlateExp(cellFile, filenamePrefix + i, lambda, numWellsOnPlate,
concentrationsToUse,dropOutRate);
}
else if (line.hasOption("pop")) {
populations = Stream.of(line.getOptionValues("pop"))
.mapToInt(Integer::parseInt)
.boxed()
.toArray(Integer[]::new);
}
else if(line.hasOption("gaussian")){
Double stdDev = Double.valueOf(line.getOptionValue("std-dev"));
for(int i = 1; i <= numPlatesToMake; i++){
makePlate(cellFile, filenamePrefix + i, stdDev, numWellsOnPlate,
concentrationsToUse,dropOutRate);
}
else{
populations = new Integer[1];
populations[0] = 1;
}
//make the plate
Plate plate;
if (line.hasOption("poisson")) {
Double stdDev = Math.sqrt(numWells);
plate = new Plate(cells, cellFilename, numWells, populations, dropoutRate, stdDev, false);
}
else if (line.hasOption("gaussian")) {
Double stdDev = Double.parseDouble(line.getOptionValue("stddev"));
plate = new Plate(cells, cellFilename, numWells, populations, dropoutRate, stdDev, false);
}
else {
assert line.hasOption("exponential");
Double lambda = Double.parseDouble(line.getOptionValue("lambda"));
plate = new Plate(cells, cellFilename, numWells, populations, dropoutRate, lambda, true);
}
PlateFileWriter writer = new PlateFileWriter(outputFilename, plate);
writer.writePlateFile();
}
else if (line.hasOption("graph")) { //Making a graph
line = parser.parse(graphOptions, Arrays.copyOfRange(args, 1, args.length));
String cellFilename = line.getOptionValue("c");
String plateFilename = line.getOptionValue("p");
String outputFilename = line.getOptionValue("o");
//get cells
CellSample cells = getCells(cellFilename);
//get plate
Plate plate = getPlate(plateFilename);
GraphWithMapData graph;
Integer readDepth = 1;
Double readErrorRate = 0.0;
Double errorCollisionRate = 0.0;
if (line.hasOption("rd")) {
readDepth = Integer.parseInt(line.getOptionValue("rd"));
}
else if(line.hasOption("poisson")){
for(int i = 1; i <= numPlatesToMake; i++){
makePlatePoisson(cellFile, filenamePrefix + i, numWellsOnPlate,
concentrationsToUse,dropOutRate);
if (line.hasOption("err")) {
readErrorRate = Double.parseDouble(line.getOptionValue("err"));
}
if (line.hasOption("coll")) {
errorCollisionRate = Double.parseDouble(line.getOptionValue("coll"));
}
graph = Simulator.makeCDR3Graph(cells, plate, readDepth, readErrorRate, errorCollisionRate, false);
if (!line.hasOption("no-binary")) { //output binary file unless told not to
GraphDataObjectWriter writer = new GraphDataObjectWriter(outputFilename, graph, false);
writer.writeDataToFile();
}
if (line.hasOption("graphml")) { //if told to, output graphml file
GraphMLFileWriter gmlwriter = new GraphMLFileWriter(outputFilename, graph);
gmlwriter.writeGraphToFile();
}
}
else if (line.hasOption("match")) { //can add a flag for which match type in future, spit this in two
line = parser.parse(matchOptions, Arrays.copyOfRange(args, 1, args.length));
String graphFilename = line.getOptionValue("g");
String outputFilename;
if(line.hasOption("o")) {
outputFilename = line.getOptionValue("o");
}
else {
outputFilename = null;
}
Integer minThreshold = Integer.parseInt(line.getOptionValue("min"));
Integer maxThreshold = Integer.parseInt(line.getOptionValue("max"));
int minOverlapPct;
if (line.hasOption("minpct")) { //see if this filter is being used
minOverlapPct = Integer.parseInt(line.getOptionValue("minpct"));
}
else {
minOverlapPct = 0;
}
int maxOccupancyDiff;
if (line.hasOption("maxdiff")) { //see if this filter is being used
maxOccupancyDiff = Integer.parseInt(line.getOptionValue("maxdiff"));
}
else {
maxOccupancyDiff = Integer.MAX_VALUE;
}
GraphWithMapData graph = getGraph(graphFilename);
MatchingResult result = Simulator.matchCDR3s(graph, graphFilename, minThreshold, maxThreshold,
maxOccupancyDiff, minOverlapPct, false);
if(outputFilename != null){
MatchingFileWriter writer = new MatchingFileWriter(outputFilename, result);
writer.writeResultsToFile();
}
//can put a bunch of ifs for outputting various things from the MatchingResult to System.out here
//after I put those flags in the matchOptions
if(line.hasOption("print-metadata")) {
for (String k : result.getMetadata().keySet()) {
System.out.println(k + ": " + result.getMetadata().get(k));
}
}
if(line.hasOption("print-error")) {
System.out.println("pairing error rate: " + result.getPairingErrorRate());
}
if(line.hasOption("print-attempt")) {
System.out.println("pairing attempt rate: " +result.getPairingAttemptRate());
}
if(line.hasOption("print-correct")) {
System.out.println("correct pairings: " + result.getCorrectPairingCount());
}
if(line.hasOption("print-incorrect")) {
System.out.println("incorrect pairings: " + result.getIncorrectPairingCount());
}
if(line.hasOption("print-alphas")) {
System.out.println("total alphas found: " + result.getAlphaCount());
}
if(line.hasOption("print-betas")) {
System.out.println("total betas found: " + result.getBetaCount());
}
if(line.hasOption("print-time")) {
System.out.println("simulation time (seconds): " + result.getSimulationTime());
}
}
}
catch (ParseException exp) {
@@ -286,43 +239,299 @@ public class CommandLineInterface {
}
}
private static Option outputFileOption() {
Option outputFile = Option.builder("o")
.longOpt("output-file")
.hasArg()
.argName("filename")
.desc("Name of output file")
.required()
.build();
return outputFile;
}
private static Options buildMainOptions() {
Options mainOptions = new Options();
Option help = Option.builder("help")
.desc("Displays this help menu")
.build();
Option makeCells = Option.builder("cells")
.longOpt("make-cells")
.desc("Makes a cell sample file of distinct T cells")
.build();
Option makePlate = Option.builder("plate")
.longOpt("make-plate")
.desc("Makes a sample plate file. Requires a cell sample file.")
.build();
Option makeGraph = Option.builder("graph")
.longOpt("make-graph")
.desc("Makes a graph/data file. Requires a cell sample file and a sample plate file")
.build();
Option matchCDR3 = Option.builder("match")
.longOpt("match-cdr3")
.desc("Matches CDR3s. Requires a graph/data file.")
.build();
Option printVersion = Option.builder("version")
.desc("Prints the program version number to stdout").build();
OptionGroup mainGroup = new OptionGroup();
mainGroup.addOption(help);
mainGroup.addOption(printVersion);
mainGroup.addOption(makeCells);
mainGroup.addOption(makePlate);
mainGroup.addOption(makeGraph);
mainGroup.addOption(matchCDR3);
mainGroup.setRequired(true);
mainOptions.addOptionGroup(mainGroup);
return mainOptions;
}
private static Options buildCellOptions() {
Options cellOptions = new Options();
Option numCells = Option.builder("n")
.longOpt("num-cells")
.desc("The number of distinct cells to generate")
.hasArg()
.argName("number")
.required().build();
Option cdr3Diversity = Option.builder("d")
.longOpt("diversity-factor")
.desc("The factor by which unique CDR3s outnumber unique CDR1s")
.hasArg()
.argName("factor")
.required().build();
cellOptions.addOption(numCells);
cellOptions.addOption(cdr3Diversity);
cellOptions.addOption(outputFileOption());
return cellOptions;
}
private static Options buildPlateOptions() {
Options plateOptions = new Options();
Option cellFile = Option.builder("c") // add this to plate options
.longOpt("cell-file")
.desc("The cell sample file to use")
.hasArg()
.argName("filename")
.required().build();
Option numWells = Option.builder("w")// add this to plate options
.longOpt("wells")
.desc("The number of wells on the sample plate")
.hasArg()
.argName("number")
.required().build();
//options group for choosing with distribution to use
OptionGroup distributions = new OptionGroup();// add this to plate options
distributions.setRequired(true);
Option poisson = Option.builder("poisson")
.desc("Use a Poisson distribution for cell sample")
.build();
Option gaussian = Option.builder("gaussian")
.desc("Use a Gaussian distribution for cell sample")
.build();
Option exponential = Option.builder("exponential")
.desc("Use an exponential distribution for cell sample")
.build();
distributions.addOption(poisson);
distributions.addOption(gaussian);
distributions.addOption(exponential);
//options group for statistical distribution parameters
OptionGroup statParams = new OptionGroup();// add this to plate options
Option stdDev = Option.builder("stddev")
.desc("If using -gaussian flag, standard deviation for distrbution")
.hasArg()
.argName("value")
.build();
Option lambda = Option.builder("lambda")
.desc("If using -exponential flag, lambda value for distribution")
.hasArg()
.argName("value")
.build();
statParams.addOption(stdDev);
statParams.addOption(lambda);
//Option group for random plate or set populations
OptionGroup wellPopOptions = new OptionGroup(); // add this to plate options
wellPopOptions.setRequired(true);
Option randomWellPopulations = Option.builder("random")
.desc("Randomize well populations on sample plate. Takes two arguments: the minimum possible population and the maximum possible population.")
.hasArgs()
.numberOfArgs(2)
.argName("min> <max")
.build();
Option specificWellPopulations = Option.builder("pop")
.desc("The well populations for each section of the sample plate. There will be as many sections as there are populations given.")
.hasArgs()
.argName("number [number]...")
.build();
Option dropoutRate = Option.builder("err") //add this to plate options
.hasArg()
.desc("The sequence dropout rate due to amplification error. (0.0 - 1.0)")
.argName("rate")
.required()
.build();
wellPopOptions.addOption(randomWellPopulations);
wellPopOptions.addOption(specificWellPopulations);
plateOptions.addOption(cellFile);
plateOptions.addOption(numWells);
plateOptions.addOptionGroup(distributions);
plateOptions.addOptionGroup(statParams);
plateOptions.addOptionGroup(wellPopOptions);
plateOptions.addOption(dropoutRate);
plateOptions.addOption(outputFileOption());
return plateOptions;
}
private static Options buildGraphOptions() {
Options graphOptions = new Options();
Option cellFilename = Option.builder("c")
.longOpt("cell-file")
.desc("Cell sample file to use for checking pairing accuracy")
.hasArg()
.argName("filename")
.required().build();
Option plateFilename = Option.builder("p")
.longOpt("plate-filename")
.desc("Sample plate file from which to construct graph")
.hasArg()
.argName("filename")
.required().build();
Option outputGraphML = Option.builder("graphml")
.desc("(Optional) Output GraphML file")
.build();
Option outputSerializedBinary = Option.builder("nb")
.longOpt("no-binary")
.desc("(Optional) Don't output serialized binary file")
.build();
Option readDepth = Option.builder("rd")
.longOpt("read-depth")
.desc("(Optional) The number of times to read each sequence.")
.hasArg()
.argName("depth")
.build();
Option readErrorProb = Option.builder("err")
.longOpt("read-error-prob")
.desc("(Optional) The probability that a sequence will be misread. (0.0 - 1.0)")
.hasArg()
.argName("prob")
.build();
Option errorCollisionProb = Option.builder("coll")
.longOpt("error-collision-prob")
.desc("(Optional) The probability that two misreads will produce the same spurious sequence. (0.0 - 1.0)")
.hasArg()
.argName("prob")
.build();
graphOptions.addOption(cellFilename);
graphOptions.addOption(plateFilename);
graphOptions.addOption(outputFileOption());
graphOptions.addOption(outputGraphML);
graphOptions.addOption(outputSerializedBinary);
graphOptions.addOption(readDepth);
graphOptions.addOption(readErrorProb);
graphOptions.addOption(errorCollisionProb);
return graphOptions;
}
private static Options buildMatchCDR3options() {
Options matchCDR3options = new Options();
Option graphFilename = Option.builder("g")
.longOpt("graph-file")
.desc("The graph/data file to use")
.hasArg()
.argName("filename")
.required().build();
Option minOccupancyOverlap = Option.builder("min")
.desc("The minimum number of shared wells to attempt to match a sequence pair")
.hasArg()
.argName("number")
.required().build();
Option maxOccupancyOverlap = Option.builder("max")
.desc("The maximum number of shared wells to attempt to match a sequence pair")
.hasArg()
.argName("number")
.required().build();
Option minOverlapPercent = Option.builder("minpct")
.desc("(Optional) The minimum percentage of a sequence's total occupancy shared by another sequence to attempt matching. (0 - 100) ")
.hasArg()
.argName("percent")
.build();
Option maxOccupancyDifference = Option.builder("maxdiff")
.desc("(Optional) The maximum difference in total occupancy between two sequences to attempt matching.")
.hasArg()
.argName("number")
.build();
Option outputFile = Option.builder("o") //can't call the method this time, because this one's optional
.longOpt("output-file")
.hasArg()
.argName("filename")
.desc("(Optional) Name of output the output file. If not present, no file will be written.")
.build();
matchCDR3options.addOption(graphFilename)
.addOption(minOccupancyOverlap)
.addOption(maxOccupancyOverlap)
.addOption(minOverlapPercent)
.addOption(maxOccupancyDifference)
.addOption(outputFile);
//options for output to System.out
Option printAlphaCount = Option.builder().longOpt("print-alphas")
.desc("(Optional) Print the number of distinct alpha sequences to stdout.").build();
Option printBetaCount = Option.builder().longOpt("print-betas")
.desc("(Optional) Print the number of distinct beta sequences to stdout.").build();
Option printTime = Option.builder().longOpt("print-time")
.desc("(Optional) Print the total simulation time to stdout.").build();
Option printErrorRate = Option.builder().longOpt("print-error")
.desc("(Optional) Print the pairing error rate to stdout").build();
Option printAttempt = Option.builder().longOpt("print-attempt")
.desc("(Optional) Print the pairing attempt rate to stdout").build();
Option printCorrect = Option.builder().longOpt("print-correct")
.desc("(Optional) Print the number of correct pairs to stdout").build();
Option printIncorrect = Option.builder().longOpt("print-incorrect")
.desc("(Optional) Print the number of incorrect pairs to stdout").build();
Option printMetadata = Option.builder().longOpt("print-metadata")
.desc("(Optional) Print a full summary of the matching results to stdout.").build();
matchCDR3options
.addOption(printErrorRate)
.addOption(printAttempt)
.addOption(printCorrect)
.addOption(printIncorrect)
.addOption(printMetadata)
.addOption(printAlphaCount)
.addOption(printBetaCount)
.addOption(printTime);
return matchCDR3options;
}
private static CellSample getCells(String cellFilename) {
assert cellFilename != null;
CellFileReader reader = new CellFileReader(cellFilename);
return reader.getCellSample();
}
private static Plate getPlate(String plateFilename) {
assert plateFilename != null;
PlateFileReader reader = new PlateFileReader(plateFilename);
return reader.getSamplePlate();
}
private static GraphWithMapData getGraph(String graphFilename) {
assert graphFilename != null;
try{
GraphDataObjectReader reader = new GraphDataObjectReader(graphFilename, false);
return reader.getData();
}
catch (IOException ex) {
ex.printStackTrace();
return null;
}
}
//for calling from command line
public static void makeCells(String filename, Integer numCells, Integer cdr1Freq){
CellSample sample = Simulator.generateCellSample(numCells, cdr1Freq);
public static void makeCells(String filename, Integer numCells, Integer cdr1Freq) {
CellSample sample = new CellSample(numCells, cdr1Freq);
CellFileWriter writer = new CellFileWriter(filename, sample);
writer.writeCellsToFile();
}
public static void makePlateExp(String cellFile, String filename, Double lambda,
Integer numWells, Integer[] concentrations, Double dropOutRate){
CellFileReader cellReader = new CellFileReader(cellFile);
Plate samplePlate = new Plate(numWells, dropOutRate, concentrations);
samplePlate.fillWellsExponential(cellReader.getFilename(), cellReader.getCells(), lambda);
PlateFileWriter writer = new PlateFileWriter(filename, samplePlate);
writer.writePlateFile();
}
private static void makePlatePoisson(String cellFile, String filename, Integer numWells,
Integer[] concentrations, Double dropOutRate){
CellFileReader cellReader = new CellFileReader(cellFile);
Double stdDev = Math.sqrt(cellReader.getCellCount());
Plate samplePlate = new Plate(numWells, dropOutRate, concentrations);
samplePlate.fillWells(cellReader.getFilename(), cellReader.getCells(), stdDev);
PlateFileWriter writer = new PlateFileWriter(filename, samplePlate);
writer.writePlateFile();
}
private static void makePlate(String cellFile, String filename, Double stdDev,
Integer numWells, Integer[] concentrations, Double dropOutRate){
CellFileReader cellReader = new CellFileReader(cellFile);
Plate samplePlate = new Plate(numWells, dropOutRate, concentrations);
samplePlate.fillWells(cellReader.getFilename(), cellReader.getCells(), stdDev);
PlateFileWriter writer = new PlateFileWriter(filename, samplePlate);
writer.writePlateFile();
}
private static void matchCDR3s(String graphFile, Integer lowThreshold, Integer highThreshold,
Integer occupancyDifference, Integer overlapPercent) {
}
}

View File

@@ -4,10 +4,6 @@ import java.math.MathContext;
public abstract class Equations {
public static int getRandomNumber(int min, int max) {
return (int) ((Math.random() * (max - min)) + min);
}
//pValue calculation as described in original pairSEQ paper.
//Included for comparison with original results.
//Not used by BiGpairSEQ for matching.

View File

@@ -1,10 +1,12 @@
import java.io.*;
public class GraphDataObjectReader {
private GraphWithMapData data;
private String filename;
public GraphDataObjectReader(String filename) throws IOException {
public GraphDataObjectReader(String filename, boolean verbose) throws IOException {
if(!filename.matches(".*\\.ser")){
filename = filename + ".ser";
}
@@ -13,10 +15,13 @@ public class GraphDataObjectReader {
BufferedInputStream fileIn = new BufferedInputStream(new FileInputStream(filename));
ObjectInputStream in = new ObjectInputStream(fileIn))
{
System.out.println("Reading graph data from file. This may take some time");
System.out.println("File I/O time is not included in results");
if (verbose) {
System.out.println("Reading graph data from file. This may take some time");
System.out.println("File I/O time is not included in results");
}
data = (GraphWithMapData) in.readObject();
} catch (FileNotFoundException | ClassNotFoundException ex) {
System.out.println("Graph/data file " + filename + " not found.");
ex.printStackTrace();
}
}

View File

@@ -1,3 +1,5 @@
import org.jgrapht.Graph;
import java.io.BufferedOutputStream;
import java.io.FileOutputStream;
import java.io.IOException;
@@ -7,6 +9,7 @@ public class GraphDataObjectWriter {
private GraphWithMapData data;
private String filename;
private boolean verbose = true;
public GraphDataObjectWriter(String filename, GraphWithMapData data) {
if(!filename.matches(".*\\.ser")){
@@ -16,13 +19,24 @@ public class GraphDataObjectWriter {
this.data = data;
}
public GraphDataObjectWriter(String filename, GraphWithMapData data, boolean verbose) {
this.verbose = verbose;
if(!filename.matches(".*\\.ser")){
filename = filename + ".ser";
}
this.filename = filename;
this.data = data;
}
public void writeDataToFile() {
try (BufferedOutputStream bufferedOut = new BufferedOutputStream(new FileOutputStream(filename));
ObjectOutputStream out = new ObjectOutputStream(bufferedOut);
){
System.out.println("Writing graph and occupancy data to file. This may take some time.");
System.out.println("File I/O time is not included in results.");
if(verbose) {
System.out.println("Writing graph and occupancy data to file. This may take some time.");
System.out.println("File I/O time is not included in results.");
}
out.writeObject(data);
} catch (IOException ex) {
ex.printStackTrace();

View File

@@ -1,35 +0,0 @@
import org.jgrapht.graph.SimpleWeightedGraph;
import org.jgrapht.nio.graphml.GraphMLImporter;
import java.io.BufferedReader;
import java.io.IOException;
import java.nio.file.Files;
import java.nio.file.Path;
public class GraphMLFileReader {
private String filename;
private SimpleWeightedGraph graph;
public GraphMLFileReader(String filename, SimpleWeightedGraph graph) {
if(!filename.matches(".*\\.graphml")){
filename = filename + ".graphml";
}
this.filename = filename;
this.graph = graph;
try(//don't need to close reader bc of try-with-resources auto-closing
BufferedReader reader = Files.newBufferedReader(Path.of(filename));
){
GraphMLImporter<SimpleWeightedGraph, BufferedReader> importer = new GraphMLImporter<>();
importer.importGraph(graph, reader);
}
catch (IOException ex) {
System.out.println("Graph file " + filename + " not found.");
System.err.println(ex);
}
}
public SimpleWeightedGraph getGraph() { return graph; }
}

View File

@@ -1,20 +1,38 @@
import org.jgrapht.graph.DefaultWeightedEdge;
import org.jgrapht.graph.SimpleWeightedGraph;
import org.jgrapht.nio.dot.DOTExporter;
import org.jgrapht.nio.Attribute;
import org.jgrapht.nio.AttributeType;
import org.jgrapht.nio.DefaultAttribute;
import org.jgrapht.nio.graphml.GraphMLExporter;
import org.jgrapht.nio.graphml.GraphMLExporter.AttributeCategory;
import org.w3c.dom.Attr;
import java.io.BufferedWriter;
import java.io.IOException;
import java.nio.file.Files;
import java.nio.file.Path;
import java.nio.file.StandardOpenOption;
import java.util.HashMap;
import java.util.Map;
public class GraphMLFileWriter {
String filename;
SimpleWeightedGraph graph;
GraphWithMapData data;
Map<String, Attribute> graphAttributes;
public GraphMLFileWriter(String filename, GraphWithMapData data) {
if(!filename.matches(".*\\.graphml")){
filename = filename + ".graphml";
}
this.filename = filename;
this.data = data;
this.graph = data.getGraph();
graphAttributes = createGraphAttributes();
}
public GraphMLFileWriter(String filename, SimpleWeightedGraph graph) {
public GraphMLFileWriter(String filename, SimpleWeightedGraph<Vertex, DefaultWeightedEdge> graph) {
if(!filename.matches(".*\\.graphml")){
filename = filename + ".graphml";
}
@@ -22,10 +40,56 @@ public class GraphMLFileWriter {
this.graph = graph;
}
private Map<String, Attribute> createGraphAttributes(){
Map<String, Attribute> ga = new HashMap<>();
//Sample plate filename
ga.put("sample plate filename", DefaultAttribute.createAttribute(data.getSourceFilename()));
// Number of wells
ga.put("well count", DefaultAttribute.createAttribute(data.getNumWells().toString()));
//Well populations
Integer[] wellPopulations = data.getWellPopulations();
StringBuilder populationsStringBuilder = new StringBuilder();
populationsStringBuilder.append(wellPopulations[0].toString());
for(int i = 1; i < wellPopulations.length; i++){
populationsStringBuilder.append(", ");
populationsStringBuilder.append(wellPopulations[i].toString());
}
String wellPopulationsString = populationsStringBuilder.toString();
ga.put("well populations", DefaultAttribute.createAttribute(wellPopulationsString));
ga.put("read depth", DefaultAttribute.createAttribute(data.getReadDepth().toString()));
ga.put("read error rate", DefaultAttribute.createAttribute(data.getReadErrorRate().toString()));
ga.put("error collision rate", DefaultAttribute.createAttribute(data.getErrorCollisionRate().toString()));
return ga;
}
public void writeGraphToFile() {
try(BufferedWriter writer = Files.newBufferedWriter(Path.of(filename), StandardOpenOption.CREATE_NEW);
){
GraphMLExporter<SimpleWeightedGraph, BufferedWriter> exporter = new GraphMLExporter<>();
//create exporter. Let the vertex labels be the unique ids for the vertices
GraphMLExporter<Vertex, SimpleWeightedGraph<Vertex, DefaultWeightedEdge>> exporter = new GraphMLExporter<>(v -> v.getVertexLabel().toString());
//set to export weights
exporter.setExportEdgeWeights(true);
//Set graph attributes
exporter.setGraphAttributeProvider( () -> graphAttributes);
//set type, sequence, and occupancy attributes for each vertex
//NEED TO ADD NEW FIELD FOR READ COUNT
exporter.setVertexAttributeProvider( v -> {
Map<String, Attribute> attributes = new HashMap<>();
attributes.put("type", DefaultAttribute.createAttribute(v.getType().name()));
attributes.put("sequence", DefaultAttribute.createAttribute(v.getSequence()));
attributes.put("occupancy", DefaultAttribute.createAttribute(v.getOccupancy()));
attributes.put("read count", DefaultAttribute.createAttribute(v.getReadCount()));
return attributes;
});
//register the attributes
for(String s : graphAttributes.keySet()) {
exporter.registerAttribute(s, AttributeCategory.GRAPH, AttributeType.STRING);
}
exporter.registerAttribute("type", AttributeCategory.NODE, AttributeType.STRING);
exporter.registerAttribute("sequence", AttributeCategory.NODE, AttributeType.STRING);
exporter.registerAttribute("occupancy", AttributeCategory.NODE, AttributeType.STRING);
exporter.registerAttribute("read count", AttributeCategory.NODE, AttributeType.STRING);
//export the graph
exporter.exportGraph(graph, writer);
} catch(IOException ex){
System.out.println("Could not make new file named "+filename);

View File

@@ -2,89 +2,137 @@ import org.jgrapht.graph.DefaultWeightedEdge;
import org.jgrapht.graph.SimpleWeightedGraph;
import java.util.ArrayList;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
import java.util.Set;
public abstract class GraphModificationFunctions {
public interface GraphModificationFunctions {
//remove over- and under-weight edges
public static List<Integer[]> filterByOverlapThresholds(SimpleWeightedGraph<Integer, DefaultWeightedEdge> graph,
int low, int high) {
List<Integer[]> removedEdges = new ArrayList<>();
for(DefaultWeightedEdge e: graph.edgeSet()){
if ((graph.getEdgeWeight(e) > high) || (graph.getEdgeWeight(e) < low)){
Integer source = graph.getEdgeSource(e);
Integer target = graph.getEdgeTarget(e);
Integer weight = (int) graph.getEdgeWeight(e);
Integer[] edge = {source, target, weight};
removedEdges.add(edge);
//remove over- and under-weight edges, return removed edges
static Map<Vertex[], Integer> filterByOverlapThresholds(SimpleWeightedGraph<Vertex, DefaultWeightedEdge> graph,
int low, int high, boolean saveEdges) {
Map<Vertex[], Integer> removedEdges = new HashMap<>();
for (DefaultWeightedEdge e : graph.edgeSet()) {
if ((graph.getEdgeWeight(e) > high) || (graph.getEdgeWeight(e) < low)) {
if(saveEdges) {
Vertex source = graph.getEdgeSource(e);
Vertex target = graph.getEdgeTarget(e);
Integer weight = (int) graph.getEdgeWeight(e);
Vertex[] edge = {source, target};
removedEdges.put(edge, weight);
}
else {
graph.setEdgeWeight(e, 0.0);
}
}
}
for (Integer[] edge : removedEdges) {
graph.removeEdge(edge[0], edge[1]);
if(saveEdges) {
for (Vertex[] edge : removedEdges.keySet()) {
graph.removeEdge(edge[0], edge[1]);
}
}
return removedEdges;
}
//Remove edges for pairs with large occupancy discrepancy
public static List<Integer[]> filterByRelativeOccupancy(SimpleWeightedGraph<Integer, DefaultWeightedEdge> graph,
Map<Integer, Integer> alphaWellCounts,
Map<Integer, Integer> betaWellCounts,
Map<Integer, Integer> plateVtoAMap,
Map<Integer, Integer> plateVtoBMap,
Integer maxOccupancyDifference) {
List<Integer[]> removedEdges = new ArrayList<>();
//Remove edges for pairs with large occupancy discrepancy, return removed edges
static Map<Vertex[], Integer> filterByRelativeOccupancy(SimpleWeightedGraph<Vertex, DefaultWeightedEdge> graph,
Integer maxOccupancyDifference, boolean saveEdges) {
Map<Vertex[], Integer> removedEdges = new HashMap<>();
for (DefaultWeightedEdge e : graph.edgeSet()) {
Integer alphaOcc = alphaWellCounts.get(plateVtoAMap.get(graph.getEdgeSource(e)));
Integer betaOcc = betaWellCounts.get(plateVtoBMap.get(graph.getEdgeTarget(e)));
Integer alphaOcc = graph.getEdgeSource(e).getOccupancy();
Integer betaOcc = graph.getEdgeTarget(e).getOccupancy();
if (Math.abs(alphaOcc - betaOcc) >= maxOccupancyDifference) {
Integer source = graph.getEdgeSource(e);
Integer target = graph.getEdgeTarget(e);
Integer weight = (int) graph.getEdgeWeight(e);
Integer[] edge = {source, target, weight};
removedEdges.add(edge);
if (saveEdges) {
Vertex source = graph.getEdgeSource(e);
Vertex target = graph.getEdgeTarget(e);
Integer weight = (int) graph.getEdgeWeight(e);
Vertex[] edge = {source, target};
removedEdges.put(edge, weight);
}
else {
graph.setEdgeWeight(e, 0.0);
}
}
}
for (Integer[] edge : removedEdges) {
graph.removeEdge(edge[0], edge[1]);
if(saveEdges) {
for (Vertex[] edge : removedEdges.keySet()) {
graph.removeEdge(edge[0], edge[1]);
}
}
return removedEdges;
}
//Remove edges for pairs where overlap size is significantly lower than the well occupancy
public static List<Integer[]> filterByOverlapPercent(SimpleWeightedGraph<Integer, DefaultWeightedEdge> graph,
Map<Integer, Integer> alphaWellCounts,
Map<Integer, Integer> betaWellCounts,
Map<Integer, Integer> plateVtoAMap,
Map<Integer, Integer> plateVtoBMap,
Integer minOverlapPercent) {
List<Integer[]> removedEdges = new ArrayList<>();
//Remove edges for pairs where overlap size is significantly lower than the well occupancy, return removed edges
static Map<Vertex[], Integer> filterByOverlapPercent(SimpleWeightedGraph<Vertex, DefaultWeightedEdge> graph,
Integer minOverlapPercent,
boolean saveEdges) {
Map<Vertex[], Integer> removedEdges = new HashMap<>();
for (DefaultWeightedEdge e : graph.edgeSet()) {
Integer alphaOcc = alphaWellCounts.get(plateVtoAMap.get(graph.getEdgeSource(e)));
Integer betaOcc = betaWellCounts.get(plateVtoBMap.get(graph.getEdgeTarget(e)));
Integer alphaOcc = graph.getEdgeSource(e).getOccupancy();
Integer betaOcc = graph.getEdgeTarget(e).getOccupancy();
double weight = graph.getEdgeWeight(e);
double min = minOverlapPercent / 100.0;
if ((weight / alphaOcc < min) || (weight / betaOcc < min)) {
Integer source = graph.getEdgeSource(e);
Integer target = graph.getEdgeTarget(e);
Integer intWeight = (int) graph.getEdgeWeight(e);
Integer[] edge = {source, target, intWeight};
removedEdges.add(edge);
if (saveEdges) {
Vertex source = graph.getEdgeSource(e);
Vertex target = graph.getEdgeTarget(e);
Integer intWeight = (int) graph.getEdgeWeight(e);
Vertex[] edge = {source, target};
removedEdges.put(edge, intWeight);
}
else {
graph.setEdgeWeight(e, 0.0);
}
}
}
for (Integer[] edge : removedEdges) {
graph.removeEdge(edge[0], edge[1]);
if(saveEdges) {
for (Vertex[] edge : removedEdges.keySet()) {
graph.removeEdge(edge[0], edge[1]);
}
}
return removedEdges;
}
public static void addRemovedEdges(SimpleWeightedGraph<Integer, DefaultWeightedEdge> graph,
List<Integer[]> removedEdges) {
for (Integer[] edge : removedEdges) {
static Map<Vertex[], Integer> filterByRelativeReadCount (SimpleWeightedGraph<Vertex, DefaultWeightedEdge> graph, Integer threshold, boolean saveEdges) {
Map<Vertex[], Integer> removedEdges = new HashMap<>();
Boolean passes;
for (DefaultWeightedEdge e : graph.edgeSet()) {
Integer alphaReadCount = graph.getEdgeSource(e).getReadCount();
Integer betaReadCount = graph.getEdgeTarget(e).getReadCount();
passes = RelativeReadCountFilterFunction(threshold, alphaReadCount, betaReadCount);
if (!passes) {
if (saveEdges) {
Vertex source = graph.getEdgeSource(e);
Vertex target = graph.getEdgeTarget(e);
Integer intWeight = (int) graph.getEdgeWeight(e);
Vertex[] edge = {source, target};
removedEdges.put(edge, intWeight);
}
else {
graph.setEdgeWeight(e, 0.0);
}
}
}
if(saveEdges) {
for (Vertex[] edge : removedEdges.keySet()) {
graph.removeEdge(edge[0], edge[1]);
}
}
return removedEdges;
}
static Boolean RelativeReadCountFilterFunction(Integer threshold, Integer alphaReadCount, Integer betaReadCount) {
return Math.abs(alphaReadCount - betaReadCount) < threshold;
}
static void addRemovedEdges(SimpleWeightedGraph<Vertex, DefaultWeightedEdge> graph,
Map<Vertex[], Integer> removedEdges) {
for (Vertex[] edge : removedEdges.keySet()) {
DefaultWeightedEdge e = graph.addEdge(edge[0], edge[1]);
graph.setEdgeWeight(e, (double) edge[2]);
graph.setEdgeWeight(e, removedEdges.get(edge));
}
}
}

View File

@@ -6,41 +6,50 @@ import java.util.Map;
//Can't just write the graph, because I need the occupancy data too.
//Makes most sense to serialize object and write that to a file.
//Which means there's no reason to split map data and graph data up.
//Custom vertex class means a lot of the map data can now be encoded in the graph itself
public class GraphWithMapData implements java.io.Serializable {
private String sourceFilename;
private final SimpleWeightedGraph graph;
private Integer numWells;
private Integer[] wellConcentrations;
private Integer[] wellPopulations;
private Integer alphaCount;
private Integer betaCount;
private final Map<Integer, Integer> distCellsMapAlphaKey;
private final Map<Integer, Integer> plateVtoAMap;
private final Map<Integer, Integer> plateVtoBMap;
private final Map<Integer, Integer> plateAtoVMap;
private final Map<Integer, Integer> plateBtoVMap;
private final Map<Integer, Integer> alphaWellCounts;
private final Map<Integer, Integer> betaWellCounts;
private int readDepth;
private double readErrorRate;
private double errorCollisionRate;
private final Map<String, String> distCellsMapAlphaKey;
// private final Map<Integer, Integer> plateVtoAMap;
// private final Map<Integer, Integer> plateVtoBMap;
// private final Map<Integer, Integer> plateAtoVMap;
// private final Map<Integer, Integer> plateBtoVMap;
// private final Map<Integer, Integer> alphaWellCounts;
// private final Map<Integer, Integer> betaWellCounts;
private final Duration time;
public GraphWithMapData(SimpleWeightedGraph graph, Integer numWells, Integer[] wellConcentrations,
Integer alphaCount, Integer betaCount,
Map<Integer, Integer> distCellsMapAlphaKey, Map<Integer, Integer> plateVtoAMap,
Map<Integer,Integer> plateVtoBMap, Map<Integer, Integer> plateAtoVMap,
Map<Integer, Integer> plateBtoVMap, Map<Integer, Integer> alphaWellCounts,
Map<Integer, Integer> betaWellCounts, Duration time) {
Map<String, String> distCellsMapAlphaKey, Integer alphaCount, Integer betaCount,
Integer readDepth, Double readErrorRate, Double errorCollisionRate, Duration time){
// Map<Integer, Integer> plateVtoAMap,
// Map<Integer,Integer> plateVtoBMap, Map<Integer, Integer> plateAtoVMap,
// Map<Integer, Integer> plateBtoVMap, Map<Integer, Integer> alphaWellCounts,
// Map<Integer, Integer> betaWellCounts,) {
this.graph = graph;
this.numWells = numWells;
this.wellConcentrations = wellConcentrations;
this.wellPopulations = wellConcentrations;
this.alphaCount = alphaCount;
this.betaCount = betaCount;
this.distCellsMapAlphaKey = distCellsMapAlphaKey;
this.plateVtoAMap = plateVtoAMap;
this.plateVtoBMap = plateVtoBMap;
this.plateAtoVMap = plateAtoVMap;
this.plateBtoVMap = plateBtoVMap;
this.alphaWellCounts = alphaWellCounts;
this.betaWellCounts = betaWellCounts;
// this.plateVtoAMap = plateVtoAMap;
// this.plateVtoBMap = plateVtoBMap;
// this.plateAtoVMap = plateAtoVMap;
// this.plateBtoVMap = plateBtoVMap;
// this.alphaWellCounts = alphaWellCounts;
// this.betaWellCounts = betaWellCounts;
this.readDepth = readDepth;
this.readErrorRate = readErrorRate;
this.errorCollisionRate = errorCollisionRate;
this.time = time;
}
@@ -52,8 +61,8 @@ public class GraphWithMapData implements java.io.Serializable {
return numWells;
}
public Integer[] getWellConcentrations() {
return wellConcentrations;
public Integer[] getWellPopulations() {
return wellPopulations;
}
public Integer getAlphaCount() {
@@ -64,33 +73,35 @@ public class GraphWithMapData implements java.io.Serializable {
return betaCount;
}
public Map<Integer, Integer> getDistCellsMapAlphaKey() {
public Map<String, String> getDistCellsMapAlphaKey() {
return distCellsMapAlphaKey;
}
public Map<Integer, Integer> getPlateVtoAMap() {
return plateVtoAMap;
}
// public Map<Integer, Integer> getPlateVtoAMap() {
// return plateVtoAMap;
// }
//
// public Map<Integer, Integer> getPlateVtoBMap() {
// return plateVtoBMap;
// }
//
// public Map<Integer, Integer> getPlateAtoVMap() {
// return plateAtoVMap;
// }
//
// public Map<Integer, Integer> getPlateBtoVMap() {
// return plateBtoVMap;
// }
//
// public Map<Integer, Integer> getAlphaWellCounts() {
// return alphaWellCounts;
// }
//
// public Map<Integer, Integer> getBetaWellCounts() {
// return betaWellCounts;
// }
public Map<Integer, Integer> getPlateVtoBMap() {
return plateVtoBMap;
}
public Map<Integer, Integer> getPlateAtoVMap() {
return plateAtoVMap;
}
public Map<Integer, Integer> getPlateBtoVMap() {
return plateBtoVMap;
}
public Map<Integer, Integer> getAlphaWellCounts() {
return alphaWellCounts;
}
public Map<Integer, Integer> getBetaWellCounts() {
return betaWellCounts;
}
public Integer getReadDepth() { return readDepth; }
public Duration getTime() {
return time;
@@ -103,4 +114,12 @@ public class GraphWithMapData implements java.io.Serializable {
public String getSourceFilename() {
return sourceFilename;
}
public Double getReadErrorRate() {
return readErrorRate;
}
public Double getErrorCollisionRate() {
return errorCollisionRate;
}
}

View File

@@ -0,0 +1,4 @@
public enum HeapType {
FIBONACCI,
PAIRING
}

View File

@@ -1,14 +1,15 @@
import java.io.IOException;
import java.util.List;
import java.util.Scanner;
import java.util.InputMismatchException;
import java.util.*;
import java.util.regex.Matcher;
import java.util.regex.Pattern;
//
public class InteractiveInterface {
final static Scanner sc = new Scanner(System.in);
static int input;
static boolean quit = false;
private static final Random rand = BiGpairSEQ.getRand();
private static final Scanner sc = new Scanner(System.in);
private static int input;
private static boolean quit = false;
public static void startInteractive() {
@@ -26,6 +27,7 @@ public class InteractiveInterface {
//Need to re-do the CDR3/CDR1 matching to correspond to new pattern
//System.out.println("5) Generate CDR3/CDR1 occupancy graph");
//System.out.println("6) Simulate CDR3/CDR1 T cell matching");
System.out.println("8) Options");
System.out.println("9) About/Acknowledgments");
System.out.println("0) Exit");
try {
@@ -36,9 +38,10 @@ public class InteractiveInterface {
case 3 -> makeCDR3Graph();
case 4 -> matchCDR3s();
//case 6 -> matchCellsCDR1();
case 8 -> mainOptions();
case 9 -> acknowledge();
case 0 -> quit = true;
default -> throw new InputMismatchException("Invalid input.");
default -> System.out.println("Invalid input.");
}
} catch (InputMismatchException | IOException ex) {
System.out.println(ex);
@@ -71,10 +74,15 @@ public class InteractiveInterface {
System.out.println(ex);
sc.next();
}
CellSample sample = Simulator.generateCellSample(numCells, cdr1Freq);
CellSample sample = new CellSample(numCells, cdr1Freq);
assert filename != null;
System.out.println("Writing cells to file");
CellFileWriter writer = new CellFileWriter(filename, sample);
writer.writeCellsToFile();
System.out.println("Cell sample written to: " + filename);
if(BiGpairSEQ.cacheCells()) {
BiGpairSEQ.setCellSampleInMemory(sample, filename);
}
}
//Output a CSV of sample plate
@@ -84,7 +92,7 @@ public class InteractiveInterface {
Double stdDev = 0.0;
Integer numWells = 0;
Integer numSections;
Integer[] concentrations = {1};
Integer[] populations = {1};
Double dropOutRate = 0.0;
boolean poisson = false;
boolean exponential = false;
@@ -123,10 +131,11 @@ public class InteractiveInterface {
}
case 3 -> {
exponential = true;
System.out.println("Please enter lambda value for exponential distribution.");
System.out.print("Please enter lambda value for exponential distribution: ");
lambda = sc.nextDouble();
if (lambda <= 0.0) {
throw new InputMismatchException("Value must be positive.");
lambda = 0.6;
System.out.println("Value must be positive. Defaulting to 0.6.");
}
}
default -> {
@@ -139,22 +148,57 @@ public class InteractiveInterface {
if(numWells < 1){
throw new InputMismatchException("No wells on plate");
}
System.out.println("\nThe plate can be evenly sectioned to allow multiple concentrations of T-cells/well");
System.out.println("How many sections would you like to make (minimum 1)?");
numSections = sc.nextInt();
if(numSections < 1) {
throw new InputMismatchException("Too few sections.");
//choose whether to make T cell population/well random
boolean randomWellPopulations;
System.out.println("Randomize number of T cells in each well? (y/n)");
String ans = sc.next();
Pattern pattern = Pattern.compile("(?:yes|y)", Pattern.CASE_INSENSITIVE);
Matcher matcher = pattern.matcher(ans);
if(matcher.matches()){
randomWellPopulations = true;
}
else if (numSections > numWells) {
throw new InputMismatchException("Cannot have more sections than wells.");
else{
randomWellPopulations = false;
}
int i = 1;
concentrations = new Integer[numSections];
while(numSections > 0) {
System.out.print("Enter number of T-cells per well in section " + i +": ");
concentrations[i - 1] = sc.nextInt();
i++;
numSections--;
if(randomWellPopulations) { //if T cell population/well is random
numSections = numWells;
Integer minPop;
Integer maxPop;
System.out.print("Please enter minimum number of T cells in a well: ");
minPop = sc.nextInt();
if(minPop < 1) {
throw new InputMismatchException("Minimum well population must be positive");
}
System.out.println("Please enter maximum number of T cells in a well: ");
maxPop = sc.nextInt();
if(maxPop < minPop) {
throw new InputMismatchException("Max well population must be greater than min well population");
}
//maximum should be inclusive, so need to add one to max of randomly generated values
populations = rand.ints(minPop, maxPop + 1)
.limit(numSections)
.boxed()
.toArray(Integer[]::new);
System.out.print("Populations: ");
System.out.println(Arrays.toString(populations));
}
else{ //if T cell population/well is not random
System.out.println("\nThe plate can be evenly sectioned to allow different numbers of T cells per well.");
System.out.println("How many sections would you like to make (minimum 1)?");
numSections = sc.nextInt();
if (numSections < 1) {
throw new InputMismatchException("Too few sections.");
} else if (numSections > numWells) {
throw new InputMismatchException("Cannot have more sections than wells.");
}
int i = 1;
populations = new Integer[numSections];
while (numSections > 0) {
System.out.print("Enter number of T cells per well in section " + i + ": ");
populations[i - 1] = sc.nextInt();
i++;
numSections--;
}
}
System.out.println("\nErrors in amplification can induce a well dropout rate for sequences");
System.out.print("Enter well dropout rate (0.0 to 1.0): ");
@@ -166,26 +210,38 @@ public class InteractiveInterface {
System.out.println(ex);
sc.next();
}
System.out.println("Reading Cell Sample file: " + cellFile);
assert cellFile != null;
CellFileReader cellReader = new CellFileReader(cellFile);
CellSample cells;
if (cellFile.equals(BiGpairSEQ.getCellFilename())){
cells = BiGpairSEQ.getCellSampleInMemory();
}
else {
System.out.println("Reading Cell Sample file: " + cellFile);
CellFileReader cellReader = new CellFileReader(cellFile);
cells = cellReader.getCellSample();
if(BiGpairSEQ.cacheCells()) {
BiGpairSEQ.setCellSampleInMemory(cells, cellFile);
}
}
assert filename != null;
Plate samplePlate;
PlateFileWriter writer;
if(exponential){
Plate samplePlate = new Plate(numWells, dropOutRate, concentrations);
samplePlate.fillWellsExponential(cellReader.getFilename(), cellReader.getCells(), lambda);
PlateFileWriter writer = new PlateFileWriter(filename, samplePlate);
writer.writePlateFile();
samplePlate = new Plate(cells, cellFile, numWells, populations, dropOutRate, lambda, true);
writer = new PlateFileWriter(filename, samplePlate);
}
else {
if (poisson) {
stdDev = Math.sqrt(cellReader.getCellCount()); //gaussian with square root of elements approximates poisson
stdDev = Math.sqrt(cells.getCellCount()); //gaussian with square root of elements approximates poisson
}
Plate samplePlate = new Plate(numWells, dropOutRate, concentrations);
samplePlate.fillWells(cellReader.getFilename(), cellReader.getCells(), stdDev);
assert filename != null;
PlateFileWriter writer = new PlateFileWriter(filename, samplePlate);
System.out.println("Writing Sample Plate to file");
writer.writePlateFile();
System.out.println("Sample Plate written to file: " + filename);
samplePlate = new Plate(cells, cellFile, numWells, populations, dropOutRate, stdDev, false);
writer = new PlateFileWriter(filename, samplePlate);
}
System.out.println("Writing Sample Plate to file");
writer.writePlateFile();
System.out.println("Sample Plate written to file: " + filename);
if(BiGpairSEQ.cachePlate()) {
BiGpairSEQ.setPlateInMemory(samplePlate, filename);
}
}
@@ -194,7 +250,11 @@ public class InteractiveInterface {
String filename = null;
String cellFile = null;
String plateFile = null;
Boolean simulateReadDepth = false;
//number of times to read each sequence in a well
int readDepth = 1;
double readErrorRate = 0.0;
double errorCollisionRate = 0.0;
try {
String str = "\nGenerating bipartite weighted graph encoding occupancy overlap data ";
str = str.concat("\nrequires a cell sample file and a sample plate file.");
@@ -203,21 +263,73 @@ public class InteractiveInterface {
cellFile = sc.next();
System.out.print("\nPlease enter name of an existing sample plate file: ");
plateFile = sc.next();
System.out.println("\nThe graph and occupancy data will be written to a serialized binary file.");
System.out.println("\nEnable simulation of sequence read depth and sequence read errors? (y/n)");
System.out.println("NOTE: sample plate data cannot be cached when simulating read errors");
String ans = sc.next();
Pattern pattern = Pattern.compile("(?:yes|y)", Pattern.CASE_INSENSITIVE);
Matcher matcher = pattern.matcher(ans);
if(matcher.matches()){
simulateReadDepth = true;
}
if (simulateReadDepth) {
BiGpairSEQ.setCachePlate(false);
BiGpairSEQ.clearPlateInMemory();
System.out.print("\nPlease enter read depth (the integer number of reads per sequence): ");
readDepth = sc.nextInt();
if(readDepth < 1) {
throw new InputMismatchException("The read depth must be an integer >= 1");
}
System.out.print("\nPlease enter probability of a sequence read error (0.0 to 1.0): ");
readErrorRate = sc.nextDouble();
if(readErrorRate < 0.0 || readErrorRate > 1.0) {
throw new InputMismatchException("The read error rate must be in the range [0.0, 1.0]");
}
System.out.println("\nPlease enter the probability of read error collision");
System.out.println("(the likelihood that two read errors produce the same spurious sequence)");
System.out.print("(0.0 to 1.0): ");
errorCollisionRate = sc.nextDouble();
if(errorCollisionRate < 0.0 || errorCollisionRate > 1.0) {
throw new InputMismatchException("The error collision probability must be an in the range [0.0, 1.0]");
}
}
System.out.println("\nThe graph and occupancy data will be written to a file.");
System.out.print("Please enter a name for the output file: ");
filename = sc.next();
} catch (InputMismatchException ex) {
System.out.println(ex);
sc.next();
}
System.out.println("Reading Cell Sample file: " + cellFile);
assert cellFile != null;
CellFileReader cellReader = new CellFileReader(cellFile);
System.out.println("Reading Sample Plate file: " + plateFile);
CellSample cellSample;
//check if cells are already in memory
if(cellFile.equals(BiGpairSEQ.getCellFilename()) && BiGpairSEQ.getCellSampleInMemory() != null) {
cellSample = BiGpairSEQ.getCellSampleInMemory();
}
else {
System.out.println("Reading Cell Sample file: " + cellFile);
CellFileReader cellReader = new CellFileReader(cellFile);
cellSample = cellReader.getCellSample();
if(BiGpairSEQ.cacheCells()) {
BiGpairSEQ.setCellSampleInMemory(cellSample, cellFile);
}
}
assert plateFile != null;
PlateFileReader plateReader = new PlateFileReader(plateFile);
Plate plate = new Plate(plateReader.getFilename(), plateReader.getWells());
if (cellReader.getCells().size() == 0){
Plate plate;
//check if plate is already in memory
if(plateFile.equals(BiGpairSEQ.getPlateFilename())){
plate = BiGpairSEQ.getPlateInMemory();
}
else {
System.out.println("Reading Sample Plate file: " + plateFile);
PlateFileReader plateReader = new PlateFileReader(plateFile);
plate = plateReader.getSamplePlate();
if(BiGpairSEQ.cachePlate()) {
BiGpairSEQ.setPlateInMemory(plate, plateFile);
}
}
if (cellSample.getCells().size() == 0){
System.out.println("No cell sample found.");
System.out.println("Returning to main menu.");
}
@@ -226,15 +338,22 @@ public class InteractiveInterface {
System.out.println("Returning to main menu.");
}
else{
List<Integer[]> cells = cellReader.getCells();
GraphWithMapData data = Simulator.makeGraph(cells, plate, true);
GraphWithMapData data = Simulator.makeCDR3Graph(cellSample, plate, readDepth, readErrorRate, errorCollisionRate, true);
assert filename != null;
GraphDataObjectWriter dataWriter = new GraphDataObjectWriter(filename, data);
dataWriter.writeDataToFile();
System.out.println("Graph and Data file written to: " + filename);
BiGpairSEQ.setGraph(data);
BiGpairSEQ.setGraphFilename(filename);
System.out.println("Graph and Data file " + filename + " cached.");
if(BiGpairSEQ.outputBinary()) {
GraphDataObjectWriter dataWriter = new GraphDataObjectWriter(filename, data);
dataWriter.writeDataToFile();
System.out.println("Serialized binary graph/data file written to: " + filename);
}
if(BiGpairSEQ.outputGraphML()) {
GraphMLFileWriter graphMLWriter = new GraphMLFileWriter(filename, data);
graphMLWriter.writeGraphToFile();
System.out.println("GraphML file written to: " + filename);
}
if(BiGpairSEQ.cacheGraph()) {
BiGpairSEQ.setGraphInMemory(data, filename);
}
}
}
@@ -256,17 +375,28 @@ public class InteractiveInterface {
System.out.println("\nWhat is the minimum number of CDR3 alpha/beta overlap wells to attempt matching?");
lowThreshold = sc.nextInt();
if(lowThreshold < 1){
throw new InputMismatchException("Minimum value for low threshold set to 1");
lowThreshold = 1;
System.out.println("Value for low occupancy overlap threshold must be positive");
System.out.println("Value for low occupancy overlap threshold set to 1");
}
System.out.println("\nWhat is the maximum number of CDR3 alpha/beta overlap wells to attempt matching?");
highThreshold = sc.nextInt();
System.out.println("\nWhat is the maximum difference in alpha/beta occupancy to attempt matching?");
maxOccupancyDiff = sc.nextInt();
System.out.println("\nWell overlap percentage = pair overlap / sequence occupancy");
System.out.println("What is the minimum well overlap percentage to attempt matching? (0 to 100)");
if(highThreshold < lowThreshold) {
highThreshold = lowThreshold;
System.out.println("Value for high occupancy overlap threshold must be >= low overlap threshold");
System.out.println("Value for high occupancy overlap threshold set to " + lowThreshold);
}
System.out.println("What is the minimum percentage of a sequence's wells in alpha/beta overlap to attempt matching? (0 - 100)");
minOverlapPercent = sc.nextInt();
if (minOverlapPercent < 0 || minOverlapPercent > 100) {
throw new InputMismatchException("Value outside range. Minimum percent set to 0");
System.out.println("Value outside range. Minimum occupancy overlap percentage set to 0");
}
System.out.println("\nWhat is the maximum difference in alpha/beta occupancy to attempt matching?");
maxOccupancyDiff = sc.nextInt();
if (maxOccupancyDiff < 0) {
maxOccupancyDiff = 0;
System.out.println("Maximum allowable difference in alpha/beta occupancy must be nonnegative");
System.out.println("Maximum allowable difference in alpha/beta occupancy set to 0");
}
} catch (InputMismatchException ex) {
System.out.println(ex);
@@ -275,17 +405,15 @@ public class InteractiveInterface {
assert graphFilename != null;
//check if this is the same graph we already have in memory.
GraphWithMapData data;
if(!(graphFilename.equals(BiGpairSEQ.getGraphFilename())) || BiGpairSEQ.getGraph() == null) {
BiGpairSEQ.clearGraph();
//read object data from file
GraphDataObjectReader dataReader = new GraphDataObjectReader(graphFilename);
data = dataReader.getData();
//set new graph in memory and new filename
BiGpairSEQ.setGraph(data);
BiGpairSEQ.setGraphFilename(graphFilename);
if(graphFilename.equals(BiGpairSEQ.getGraphFilename())) {
data = BiGpairSEQ.getGraphInMemory();
}
else {
data = BiGpairSEQ.getGraph();
GraphDataObjectReader dataReader = new GraphDataObjectReader(graphFilename, true);
data = dataReader.getData();
if(BiGpairSEQ.cacheGraph()) {
BiGpairSEQ.setGraphInMemory(data, graphFilename);
}
}
//simulate matching
MatchingResult results = Simulator.matchCDR3s(data, graphFilename, lowThreshold, highThreshold, maxOccupancyDiff,
@@ -402,7 +530,82 @@ public class InteractiveInterface {
// }
// }
private static void mainOptions(){
boolean backToMain = false;
while(!backToMain) {
System.out.println("\n--------------OPTIONS---------------");
System.out.println("1) Turn " + getOnOff(!BiGpairSEQ.cacheCells()) + " cell sample file caching");
System.out.println("2) Turn " + getOnOff(!BiGpairSEQ.cachePlate()) + " plate file caching");
System.out.println("3) Turn " + getOnOff(!BiGpairSEQ.cacheGraph()) + " graph/data file caching");
System.out.println("4) Turn " + getOnOff(!BiGpairSEQ.outputBinary()) + " serialized binary graph output");
System.out.println("5) Turn " + getOnOff(!BiGpairSEQ.outputGraphML()) + " GraphML graph output (for data portability to other programs)");
System.out.println("6) Maximum weight matching algorithm options");
System.out.println("0) Return to main menu");
try {
input = sc.nextInt();
switch (input) {
case 1 -> BiGpairSEQ.setCacheCells(!BiGpairSEQ.cacheCells());
case 2 -> BiGpairSEQ.setCachePlate(!BiGpairSEQ.cachePlate());
case 3 -> BiGpairSEQ.setCacheGraph(!BiGpairSEQ.cacheGraph());
case 4 -> BiGpairSEQ.setOutputBinary(!BiGpairSEQ.outputBinary());
case 5 -> BiGpairSEQ.setOutputGraphML(!BiGpairSEQ.outputGraphML());
case 6 -> algorithmOptions();
case 0 -> backToMain = true;
default -> System.out.println("Invalid input");
}
} catch (InputMismatchException ex) {
System.out.println(ex);
sc.next();
}
}
}
/**
* Helper function for printing menu items in mainOptions(). Returns a string based on the value of parameter.
*
* @param b - a boolean value
* @return String "on" if b is true, "off" if b is false
*/
private static String getOnOff(boolean b) {
if (b) { return "on";}
else { return "off"; }
}
private static void algorithmOptions(){
boolean backToOptions = false;
while(!backToOptions) {
System.out.println("\n---------ALGORITHM OPTIONS----------");
System.out.println("1) Use scaling algorithm by Duan and Su.");
System.out.println("2) Use LEDA book algorithm with Fibonacci heap priority queue");
System.out.println("3) Use LEDA book algorithm with pairing heap priority queue");
System.out.println("0) Return to Options menu");
try {
input = sc.nextInt();
switch (input) {
case 1 -> System.out.println("This option is not yet implemented. Choose another.");
case 2 -> {
BiGpairSEQ.setFibonacciHeap();
System.out.println("MWM algorithm set to LEDA with Fibonacci heap");
backToOptions = true;
}
case 3 -> {
BiGpairSEQ.setPairingHeap();
System.out.println("MWM algorithm set to LEDA with pairing heap");
backToOptions = true;
}
case 0 -> backToOptions = true;
default -> System.out.println("Invalid input");
}
} catch (InputMismatchException ex) {
System.out.println(ex);
sc.next();
}
}
}
private static void acknowledge(){
System.out.println("BiGpairSEQ_Sim " + BiGpairSEQ.getVersion());
System.out.println();
System.out.println("This program simulates BiGpairSEQ, a graph theory based adaptation");
System.out.println("of the pairSEQ algorithm for pairing T cell receptor sequences.");
System.out.println();

View File

@@ -9,27 +9,34 @@ public class MatchingResult {
private final List<String> comments;
private final List<String> headers;
private final List<List<String>> allResults;
private final Map<Integer, Integer> matchMap;
private final Duration time;
private final Map<String, String> matchMap;
public MatchingResult(Map<String, String> metadata, List<String> headers,
List<List<String>> allResults, Map<Integer, Integer>matchMap, Duration time){
List<List<String>> allResults, Map<String, String>matchMap){
/*
* POSSIBLE KEYS FOR METADATA MAP ARE:
* sample plate filename *
* graph filename *
* matching weight *
* well populations *
* total alphas found *
* total betas found *
* high overlap threshold
* low overlap threshold
* maximum occupancy difference
* minimum overlap percent
* pairing attempt rate
* correct pairing count
* incorrect pairing count
* pairing error rate
* simulation time
* sequence read depth *
* sequence read error rate *
* read error collision rate *
* total alphas read from plate *
* total betas read from plate *
* alphas in graph (after pre-filtering) *
* betas in graph (after pre-filtering) *
* high overlap threshold for pairing *
* low overlap threshold for pairing *
* maximum occupancy difference for pairing *
* minimum overlap percent for pairing *
* pairing attempt rate *
* correct pairing count *
* incorrect pairing count *
* pairing error rate *
* time to generate graph (seconds) *
* time to pair sequences (seconds) *
* total simulation time (seconds) *
*/
this.metadata = metadata;
this.comments = new ArrayList<>();
@@ -39,8 +46,6 @@ public class MatchingResult {
this.headers = headers;
this.allResults = allResults;
this.matchMap = matchMap;
this.time = time;
}
public Map<String, String> getMetadata() {return metadata;}
@@ -57,13 +62,13 @@ public class MatchingResult {
return headers;
}
public Map<Integer, Integer> getMatchMap() {
public Map<String, String> getMatchMap() {
return matchMap;
}
public Duration getTime() {
return time;
}
// public Duration getTime() {
// return time;
// }
public String getPlateFilename() {
return metadata.get("sample plate filename");
@@ -84,13 +89,29 @@ public class MatchingResult {
}
public Integer getAlphaCount() {
return Integer.parseInt(metadata.get("total alpha count"));
return Integer.parseInt(metadata.get("total alphas read from plate"));
}
public Integer getBetaCount() {
return Integer.parseInt(metadata.get("total beta count"));
return Integer.parseInt(metadata.get("total betas read from plate"));
}
//put in the rest of these methods following the same pattern
public Integer getHighOverlapThreshold() { return Integer.parseInt(metadata.get("high overlap threshold for pairing"));}
public Integer getLowOverlapThreshold() { return Integer.parseInt(metadata.get("low overlap threshold for pairing"));}
public Integer getMaxOccupancyDifference() { return Integer.parseInt(metadata.get("maximum occupancy difference for pairing"));}
public Integer getMinOverlapPercent() { return Integer.parseInt(metadata.get("minimum overlap percent for pairing"));}
public Double getPairingAttemptRate() { return Double.parseDouble(metadata.get("pairing attempt rate"));}
public Integer getCorrectPairingCount() { return Integer.parseInt(metadata.get("correct pairing count"));}
public Integer getIncorrectPairingCount() { return Integer.parseInt(metadata.get("incorrect pairing count"));}
public Double getPairingErrorRate() { return Double.parseDouble(metadata.get("pairing error rate"));}
public String getSimulationTime() { return metadata.get("total simulation time (seconds)"); }
}

View File

@@ -5,12 +5,15 @@ TODO: Implement exponential distribution using inversion method - DONE
TODO: Implement discrete frequency distributions using Vose's Alias Method
*/
import java.util.*;
public class Plate {
private CellSample cells;
private String sourceFile;
private List<List<Integer[]>> wells;
private Random rand = new Random();
private String filename;
private List<List<String[]>> wells;
private final Random rand = BiGpairSEQ.getRand();
private int size;
private double error;
private Integer[] populations;
@@ -18,6 +21,25 @@ public class Plate {
private double lambda;
boolean exponential = false;
public Plate(CellSample cells, String cellFilename, int numWells, Integer[] populations,
double dropoutRate, double stdDev_or_lambda, boolean exponential){
this.cells = cells;
this.sourceFile = cellFilename;
this.size = numWells;
this.wells = new ArrayList<>();
this.error = dropoutRate;
this.populations = populations;
this.exponential = exponential;
if (this.exponential) {
this.lambda = stdDev_or_lambda;
fillWellsExponential(cells.getCells(), this.lambda);
}
else {
this.stdDev = stdDev_or_lambda;
fillWells(cells.getCells(), this.stdDev);
}
}
public Plate(int size, double error, Integer[] populations) {
this.size = size;
@@ -26,13 +48,14 @@ public class Plate {
wells = new ArrayList<>();
}
public Plate(String sourceFileName, List<List<Integer[]>> wells) {
this.sourceFile = sourceFileName;
//constructor for returning a Plate from a PlateFileReader
public Plate(String filename, List<List<String[]>> wells) {
this.filename = filename;
this.wells = wells;
this.size = wells.size();
List<Integer> concentrations = new ArrayList<>();
for (List<Integer[]> w: wells) {
for (List<String[]> w: wells) {
if(!concentrations.contains(w.size())){
concentrations.add(w.size());
}
@@ -43,35 +66,26 @@ public class Plate {
}
}
public void fillWellsExponential(String sourceFileName, List<Integer[]> cells, double lambda){
private void fillWellsExponential(List<String[]> cells, double lambda){
this.lambda = lambda;
exponential = true;
sourceFile = sourceFileName;
int numSections = populations.length;
int section = 0;
double m;
int n;
int test=0;
while (section < numSections){
for (int i = 0; i < (size / numSections); i++) {
List<Integer[]> well = new ArrayList<>();
List<String[]> well = new ArrayList<>();
for (int j = 0; j < populations[section]; j++) {
do {
//inverse transform sampling: for random number u in [0,1), x = log(1-u) / (-lambda)
m = (Math.log10((1 - rand.nextDouble()))/(-lambda)) * Math.sqrt(cells.size());
} while (m >= cells.size() || m < 0);
n = (int) Math.floor(m);
//n = Equations.getRandomNumber(0, cells.size());
// was testing generating the cell sample file with exponential dist, then sampling flat here
//that would be more realistic
//But would mess up other things in the simulation with how I've coded it.
if(n > test){
test = n;
}
Integer[] cellToAdd = cells.get(n).clone();
String[] cellToAdd = cells.get(n).clone();
for(int k = 0; k < cellToAdd.length; k++){
if(Math.abs(rand.nextDouble()) < error){//error applied to each seqeunce
cellToAdd[k] = -1;
if(Math.abs(rand.nextDouble()) <= error){//error applied to each sequence
cellToAdd[k] = "-1";
}
}
well.add(cellToAdd);
@@ -80,28 +94,26 @@ public class Plate {
}
section++;
}
System.out.println("Highest index: " +test);
}
public void fillWells(String sourceFileName, List<Integer[]> cells, double stdDev) {
private void fillWells( List<String[]> cells, double stdDev) {
this.stdDev = stdDev;
sourceFile = sourceFileName;
int numSections = populations.length;
int section = 0;
double m;
int n;
while (section < numSections){
for (int i = 0; i < (size / numSections); i++) {
List<Integer[]> well = new ArrayList<>();
List<String[]> well = new ArrayList<>();
for (int j = 0; j < populations[section]; j++) {
do {
m = (rand.nextGaussian() * stdDev) + (cells.size() / 2);
} while (m >= cells.size() || m < 0);
n = (int) Math.floor(m);
Integer[] cellToAdd = cells.get(n).clone();
String[] cellToAdd = cells.get(n).clone();
for(int k = 0; k < cellToAdd.length; k++){
if(Math.abs(rand.nextDouble()) < error){//error applied to each sequence
cellToAdd[k] = -1;
cellToAdd[k] = "-1";
}
}
well.add(cellToAdd);
@@ -132,40 +144,188 @@ public class Plate {
return error;
}
public List<List<Integer[]>> getWells() {
public List<List<String[]>> getWells() {
return wells;
}
//returns a map of the counts of the sequence at cell index sIndex, in all wells
public Map<Integer, Integer> assayWellsSequenceS(int... sIndices){
return this.assayWellsSequenceS(0, size, sIndices);
}
// //returns a map of the counts of the sequence at cell index sIndex, in all wells
// public void assayWellsSequenceS(Map<String, Integer> sequences, int... sIndices){
// this.assayWellsSequenceS(sequences, 0, size, sIndices);
// }
//
// //returns a map of the counts of the sequence at cell index sIndex, in a specific well
// public void assayWellsSequenceS(Map<String, Integer> sequences, int n, int... sIndices) {
// this.assayWellsSequenceS(sequences, n, n+1, sIndices);
// }
//
// //returns a map of the counts of the sequence at cell index sIndex, in a range of wells
// public void assayWellsSequenceS(Map<String, Integer> sequences, int start, int end, int... sIndices) {
// for(int sIndex: sIndices){
// for(int i = start; i < end; i++){
// countSequences(sequences, wells.get(i), sIndex);
// }
// }
// }
// //For the sequences at cell indices sIndices, counts number of unique sequences in the given well into the given map
// private void countSequences(Map<String, Integer> wellMap, List<String[]> well, int... sIndices) {
// for(String[] cell : well) {
// for(int sIndex: sIndices){
// //skip dropout sequences, which have value -1
// if(!"-1".equals(cell[sIndex])){
// wellMap.merge(cell[sIndex], 1, (oldValue, newValue) -> oldValue + newValue);
// }
// }
// }
// }
//returns a map of the counts of the sequence at cell index sIndex, in a specific well
public Map<Integer, Integer> assayWellsSequenceS(int n, int... sIndices) { return this.assayWellsSequenceS(n, n+1, sIndices);}
//returns a map of the counts of the sequence at cell index sIndex, in a range of wells
public Map<Integer, Integer> assayWellsSequenceS(int start, int end, int... sIndices) {
Map<Integer,Integer> assay = new HashMap<>();
for(int pIndex: sIndices){
for(int i = start; i < end; i++){
countSequences(assay, wells.get(i), pIndex);
}
}
return assay;
}
//For the sequences at cell indices sIndices, counts number of unique sequences in the given well into the given map
private void countSequences(Map<Integer, Integer> wellMap, List<Integer[]> well, int... sIndices) {
for(Integer[] cell : well) {
for(int sIndex: sIndices){
if(cell[sIndex] != -1){
wellMap.merge(cell[sIndex], 1, (oldValue, newValue) -> oldValue + newValue);
//For the sequences at cell indices sIndices, counts number of unique sequences in all well into the given map
public Map<String, SequenceRecord> countSequences(Integer readDepth, Double readErrorRate,
Double errorCollisionRate, int... sIndices) {
SequenceType[] sequenceTypes = EnumSet.allOf(SequenceType.class).toArray(new SequenceType[0]);
Map<String, Integer> distinctMisreadCounts = new HashMap<>();
Map<String, SequenceRecord> sequenceMap = new LinkedHashMap<>();
for (int well = 0; well < size; well++) {
for (String[] cell : wells.get(well)) {
for (int sIndex : sIndices) {
//skip dropout sequences, which have value -1
if (!"-1".equals(cell[sIndex])) {
for (int j = 0; j < readDepth; j++) {
//Misread sequence
if (rand.nextDouble() < readErrorRate) {
StringBuilder spurious = new StringBuilder(cell[sIndex]);
//if this sequence hasn't been misread before, or the read error is unique,
//append one more "*" than has been appended before
if (rand.nextDouble() > errorCollisionRate || !distinctMisreadCounts.containsKey(cell[sIndex])) {
distinctMisreadCounts.merge(cell[sIndex], 1, (oldValue, newValue) -> oldValue + newValue);
for (int k = 0; k < distinctMisreadCounts.get(cell[sIndex]); k++) {
spurious.append("*");
}
SequenceRecord tmp = new SequenceRecord(spurious.toString(), sequenceTypes[sIndex]);
tmp.addRead(well);
sequenceMap.put(spurious.toString(), tmp);
}
//if this is a read error collision, randomly choose a number of "*"s that has been appended before
else {
int starCount = rand.nextInt(distinctMisreadCounts.get(cell[sIndex]));
for (int k = 0; k < starCount; k++) {
spurious.append("*");
}
sequenceMap.get(spurious.toString()).addRead(well);
}
}
//sequence is read correctly
else {
if (!sequenceMap.containsKey(cell[sIndex])) {
SequenceRecord tmp = new SequenceRecord(cell[sIndex], sequenceTypes[sIndex]);
tmp.addRead(well);
sequenceMap.put(cell[sIndex], tmp);
} else {
sequenceMap.get(cell[sIndex]).addRead(well);
}
}
}
}
}
}
}
return sequenceMap;
}
// //returns a map of the counts of the sequence at cell index sIndex, in all wells
// //Simulates read depth and read errors, counts the number of reads of a unique sequence into the given map.
// public void assayWellsSequenceSWithReadDepth(Map<String, Integer> misreadCounts, Map<String, Integer> occupancyMap, Map<String, Integer> readCountMap,
// int readDepth, double readErrorProb, double errorCollisionProb, int... sIndices) {
// this.assayWellsSequenceSWithReadDepth(misreadCounts, occupancyMap, readCountMap, readDepth, readErrorProb, errorCollisionProb, 0, size, sIndices);
// }
// //returns a map of the counts of the sequence at cell index sIndex, in a specific of wells
// //Simulates read depth and read errors, counts the number of reads of a unique sequence into the given map.
// public void assayWellsSequenceSWithReadDepth(Map<String, Integer> misreadCounts, Map<String, Integer> occupancyMap, Map<String, Integer> readCountMap,
// int readDepth, double readErrorProb, double errorCollisionProb,
// int n, int... sIndices) {
// this.assayWellsSequenceSWithReadDepth(misreadCounts, occupancyMap, readCountMap, readDepth, readErrorProb, errorCollisionProb, n, n+1, sIndices);
// }
//
// //returns a map of the counts of the sequence at cell index sIndex, in a range of wells
// //Simulates read depth and read errors, counts the number of reads of a unique sequence into the given map.
// public void assayWellsSequenceSWithReadDepth(Map<String, Integer> misreadCounts, Map<String, Integer> occupancyMap, Map<String, Integer> readCountMap,
// int readDepth, double readErrorProb, double errorCollisionProb,
// int start, int end, int... sIndices) {
// for(int sIndex: sIndices){
// for(int i = start; i < end; i++){
// countSequencesWithReadDepth(misreadCounts, occupancyMap, readCountMap, readDepth, readErrorProb, errorCollisionProb, wells.get(i), sIndex);
// }
// }
// }
//
// //For the sequences at cell indices sIndices, counts number of unique sequences in the given well into the given map
// //Simulates read depth and read errors, counts the number of reads of a unique sequence into the given map.
// //NOTE: this function changes the content of the well, adding spurious cells to contain the misread sequences
// //(this is necessary because, in the simulation, the plate is read multiple times, but random misreads can only
// //be simulated once).
// //(Possibly I should refactor all of this to only require a single plate assay, to speed things up. Or at least
// //to see if it would speed things up.)
// private void countSequencesWithReadDepth(Map<String, Integer> distinctMisreadCounts, Map<String, Integer> occupancyMap, Map<String, Integer> readCountMap,
// int readDepth, double readErrorProb, double errorCollisionProb,
// List<String[]> well, int... sIndices) {
// //list of spurious cells to add to well after counting
// List<String[]> spuriousCells = new ArrayList<>();
// for(String[] cell : well) {
// //new potential spurious cell for each cell that gets read
// String[] spuriousCell = new String[SequenceType.values().length];
// //initialize spurious cell with all dropout sequences
// Arrays.fill(spuriousCell, "-1");
// //has a read error occurred?
// boolean readError = false;
// for(int sIndex: sIndices){
// //skip dropout sequences, which have value "-1"
// if(!"-1".equals(cell[sIndex])){
// Map<String, Integer> sequencesWithReadCounts = new LinkedHashMap<>();
// for(int i = 0; i < readDepth; i++) {
// if (rand.nextDouble() <= readErrorProb) {
// readError = true;
// //Read errors are represented by appending "*"s to the end of the sequence some number of times
// StringBuilder spurious = new StringBuilder(cell[sIndex]);
// //if this sequence hasn't been misread before, or the read error is unique,
// //append one more "*" than has been appended before
// if (!distinctMisreadCounts.containsKey(cell[sIndex]) || rand.nextDouble() > errorCollisionProb) {
// distinctMisreadCounts.merge(cell[sIndex], 1, (oldValue, newValue) -> oldValue + newValue);
// for (int j = 0; j < distinctMisreadCounts.get(cell[sIndex]); j++) {
// spurious.append("*");
// }
// }
// //if this is a read error collision, randomly choose a number of "*"s that has been appended before
// else {
// int starCount = rand.nextInt(distinctMisreadCounts.get(cell[sIndex]));
// for (int j = 0; j < starCount; j++) {
// spurious.append("*");
// }
// }
// sequencesWithReadCounts.merge(spurious.toString(), 1, (oldValue, newValue) -> oldValue + newValue);
// //add spurious sequence to spurious cell
// spuriousCell[sIndex] = spurious.toString();
// }
// else {
// sequencesWithReadCounts.merge(cell[sIndex], 1, (oldValue, newValue) -> oldValue + newValue);
// }
// }
// for(String seq : sequencesWithReadCounts.keySet()) {
// occupancyMap.merge(seq, 1, (oldValue, newValue) -> oldValue + newValue);
// readCountMap.merge(seq, sequencesWithReadCounts.get(seq), (oldValue, newValue) -> oldValue + newValue);
// }
// }
// }
// if (readError) { //only add a new spurious cell if there was a read error
// spuriousCells.add(spuriousCell);
// }
// }
// //add all spurious cells to the well
// well.addAll(spuriousCells);
// }
public String getSourceFileName() {
return sourceFile;
}
public String getFilename() { return filename; }
}

View File

@@ -13,7 +13,7 @@ import java.util.regex.Pattern;
public class PlateFileReader {
private List<List<Integer[]>> wells = new ArrayList<>();
private List<List<String[]>> wells = new ArrayList<>();
private String filename;
public PlateFileReader(String filename){
@@ -32,17 +32,17 @@ public class PlateFileReader {
CSVParser parser = new CSVParser(reader, plateFileFormat);
){
for(CSVRecord record: parser.getRecords()) {
List<Integer[]> well = new ArrayList<>();
List<String[]> well = new ArrayList<>();
for(String s: record) {
if(!"".equals(s)) {
String[] intString = s.replaceAll("\\[", "")
String[] sequences = s.replaceAll("\\[", "")
.replaceAll("]", "")
.replaceAll(" ", "")
.split(",");
//System.out.println(intString);
Integer[] arr = new Integer[intString.length];
for (int i = 0; i < intString.length; i++) {
arr[i] = Integer.valueOf(intString[i]);
//System.out.println(sequences);
String[] arr = new String[sequences.length];
for (int i = 0; i < sequences.length; i++) {
arr[i] = sequences[i];
}
well.add(arr);
}
@@ -56,11 +56,8 @@ public class PlateFileReader {
}
public List<List<Integer[]>> getWells() {
return wells;
public Plate getSamplePlate() {
return new Plate(filename, wells);
}
public String getFilename() {
return filename;
}
}

View File

@@ -10,13 +10,13 @@ import java.util.*;
public class PlateFileWriter {
private int size;
private List<List<Integer[]>> wells;
private List<List<String[]>> wells;
private double stdDev;
private double lambda;
private Double error;
private String filename;
private String sourceFileName;
private Integer[] concentrations;
private Integer[] populations;
private boolean isExponential = false;
public PlateFileWriter(String filename, Plate plate) {
@@ -35,18 +35,18 @@ public class PlateFileWriter {
}
this.error = plate.getError();
this.wells = plate.getWells();
this.concentrations = plate.getPopulations();
Arrays.sort(concentrations);
this.populations = plate.getPopulations();
Arrays.sort(populations);
}
public void writePlateFile(){
Comparator<List<Integer[]>> listLengthDescending = Comparator.comparingInt(List::size);
Comparator<List<String[]>> listLengthDescending = Comparator.comparingInt(List::size);
wells.sort(listLengthDescending.reversed());
int maxLength = wells.get(0).size();
List<List<String>> wellsAsStrings = new ArrayList<>();
for (List<Integer[]> w: wells){
for (List<String[]> w: wells){
List<String> tmp = new ArrayList<>();
for(Integer[] c: w) {
for(String[] c: w) {
tmp.add(Arrays.toString(c));
}
wellsAsStrings.add(tmp);
@@ -73,14 +73,12 @@ public class PlateFileWriter {
// rows.add(tmp);
// }
//get list of well populations
List<Integer> wellPopulations = Arrays.asList(concentrations);
//make string out of populations list
//make string out of populations array
StringBuilder populationsStringBuilder = new StringBuilder();
populationsStringBuilder.append(wellPopulations.remove(0).toString());
for(Integer i: wellPopulations){
populationsStringBuilder.append(populations[0].toString());
for(int i = 1; i < populations.length; i++){
populationsStringBuilder.append(", ");
populationsStringBuilder.append(i.toString());
populationsStringBuilder.append(populations[i].toString());
}
String wellPopulationsString = populationsStringBuilder.toString();

View File

@@ -0,0 +1,65 @@
/*
Class to represent individual sequences, holding their well occupancy and read count information.
Will make a map of these keyed to the sequences themselves.
Ideally, I'll be able to construct both the Vertices and the weights matrix from this map.
*/
import java.io.Serializable;
import java.util.*;
public class SequenceRecord implements Serializable {
private final String sequence;
private final SequenceType type;
//keys are well numbers, values are read count in that well
private final Map<Integer, Integer> wells;
public SequenceRecord (String sequence, SequenceType type) {
this.sequence = sequence;
this.type = type;
this.wells = new LinkedHashMap<>();
}
//this shouldn't be necessary, since the sequence will be the map key, but
public String getSequence() {
return sequence;
}
public SequenceType getSequenceType(){
return type;
}
//use this to update the record for each new read
public void addRead(Integer wellNumber) {
wells.merge(wellNumber,1, Integer::sum);
}
//don't know if I'll ever need this
public void addWellData(Integer wellNumber, Integer readCount) {
wells.put(wellNumber, readCount);
}
public Set<Integer> getWells() {
return wells.keySet();
}
public Map<Integer, Integer> getWellOccupancies() { return wells;}
public boolean isInWell(Integer wellNumber) {
return wells.containsKey(wellNumber);
}
public Integer getOccupancy() {
return wells.size();
}
//read count for whole plate
public Integer getReadCount(){
return wells.values().stream().mapToInt(Integer::valueOf).sum();
}
//read count in a specific well
public Integer getReadCount(Integer wellNumber) {
return wells.get(wellNumber);
}
}

View File

@@ -0,0 +1,8 @@
//enum for tagging types of sequences
//Listed in order that they appear in a cell array, so ordinal() method will return correct index
public enum SequenceType {
CDR3_ALPHA,
CDR3_BETA,
CDR1_ALPHA,
CDR1_BETA
}

View File

@@ -1,9 +1,9 @@
import org.jgrapht.Graph;
import org.jgrapht.alg.interfaces.MatchingAlgorithm;
import org.jgrapht.alg.matching.MaximumWeightBipartiteMatching;
import org.jgrapht.generate.SimpleWeightedBipartiteGraphMatrixGenerator;
import org.jgrapht.graph.DefaultWeightedEdge;
import org.jgrapht.graph.SimpleWeightedGraph;
import org.jheaps.tree.FibonacciHeap;
import org.jheaps.tree.PairingHeap;
import java.math.BigDecimal;
@@ -12,130 +12,128 @@ import java.text.NumberFormat;
import java.time.Instant;
import java.time.Duration;
import java.util.*;
import java.util.stream.IntStream;
/*
Refactor notes
What would be necessary to do everything with only one scan through the sample plate?
I would need to keep a list of sequences (real and spurious), and metadata about each sequence.
I would need the data:
* # of each well the sequence appears in
* Read count in that well
*/
//NOTE: "sequence" in method and variable names refers to a peptide sequence from a simulated T cell
public class Simulator {
private static final int cdr3AlphaIndex = 0;
private static final int cdr3BetaIndex = 1;
private static final int cdr1AlphaIndex = 2;
private static final int cdr1BetaIndex = 3;
public class Simulator implements GraphModificationFunctions {
public static CellSample generateCellSample(Integer numDistinctCells, Integer cdr1Freq) {
//In real T cells, CDR1s have about one third the diversity of CDR3s
List<Integer> numbersCDR3 = new ArrayList<>();
List<Integer> numbersCDR1 = new ArrayList<>();
Integer numDistCDR3s = 2 * numDistinctCells + 1;
IntStream.range(1, numDistCDR3s + 1).forEach(i -> numbersCDR3.add(i));
IntStream.range(numDistCDR3s + 1, numDistCDR3s + 1 + (numDistCDR3s / cdr1Freq) + 1).forEach(i -> numbersCDR1.add(i));
Collections.shuffle(numbersCDR3);
Collections.shuffle(numbersCDR1);
//Each cell represented by 4 values
//two CDR3s, and two CDR1s. First two values are CDR3s (alpha, beta), second two are CDR1s (alpha, beta)
List<Integer[]> distinctCells = new ArrayList<>();
for(int i = 0; i < numbersCDR3.size() - 1; i = i + 2){
Integer tmpCDR3a = numbersCDR3.get(i);
Integer tmpCDR3b = numbersCDR3.get(i+1);
Integer tmpCDR1a = numbersCDR1.get(i % numbersCDR1.size());
Integer tmpCDR1b = numbersCDR1.get((i+1) % numbersCDR1.size());
Integer[] tmp = {tmpCDR3a, tmpCDR3b, tmpCDR1a, tmpCDR1b};
distinctCells.add(tmp);
}
return new CellSample(distinctCells, cdr1Freq);
}
//Make the graph needed for matching CDR3s
public static GraphWithMapData makeGraph(List<Integer[]> distinctCells, Plate samplePlate, boolean verbose) {
public static GraphWithMapData makeCDR3Graph(CellSample cellSample, Plate samplePlate, int readDepth,
double readErrorRate, double errorCollisionRate, boolean verbose) {
//start timing
Instant start = Instant.now();
int[] alphaIndex = {cdr3AlphaIndex};
int[] betaIndex = {cdr3BetaIndex};
int[] alphaIndices = {SequenceType.CDR3_ALPHA.ordinal()};
int[] betaIndices = {SequenceType.CDR3_BETA.ordinal()};
List<String[]> distinctCells = cellSample.getCells();
int numWells = samplePlate.getSize();
//Make a hashmap keyed to alphas, values are associated betas.
if(verbose){System.out.println("Making cell maps");}
//HashMap keyed to Alphas, values Betas
Map<Integer, Integer> distCellsMapAlphaKey = makeSequenceToSequenceMap(distinctCells, 0, 1);
Map<String, String> distCellsMapAlphaKey = makeSequenceToSequenceMap(distinctCells,
SequenceType.CDR3_ALPHA.ordinal(), SequenceType.CDR3_BETA.ordinal());
if(verbose){System.out.println("Cell maps made");}
if(verbose){System.out.println("Making well maps");}
Map<Integer, Integer> allAlphas = samplePlate.assayWellsSequenceS(alphaIndex);
Map<Integer, Integer> allBetas = samplePlate.assayWellsSequenceS(betaIndex);
int alphaCount = allAlphas.size();
if(verbose){System.out.println("All alphas count: " + alphaCount);}
int betaCount = allBetas.size();
if(verbose){System.out.println("All betas count: " + betaCount);}
if(verbose){System.out.println("Well maps made");}
//Make linkedHashMap keyed to sequences, values are SequenceRecords reflecting plate statistics
if(verbose){System.out.println("Making sample plate sequence maps");}
Map<String, SequenceRecord> alphaSequences = samplePlate.countSequences(readDepth, readErrorRate,
errorCollisionRate, alphaIndices);
int alphaCount = alphaSequences.size();
if(verbose){System.out.println("Alphas sequences read: " + alphaCount);}
Map<String, SequenceRecord> betaSequences = samplePlate.countSequences(readDepth, readErrorRate,
errorCollisionRate, betaIndices);
int betaCount = betaSequences.size();
if(verbose){System.out.println("Betas sequences read: " + betaCount);}
if(verbose){System.out.println("Sample plate sequence maps made");}
//pre-filter saturating sequences and sequences likely to be misreads
if(verbose){System.out.println("Removing sequences present in all wells.");}
filterByOccupancyThresholds(allAlphas, 1, numWells - 1);
filterByOccupancyThresholds(allBetas, 1, numWells - 1);
filterByOccupancyThresholds(alphaSequences, 1, numWells - 1);
filterByOccupancyThresholds(betaSequences, 1, numWells - 1);
if(verbose){System.out.println("Sequences removed");}
int pairableAlphaCount = allAlphas.size();
if(verbose){System.out.println("Remaining alphas count: " + pairableAlphaCount);}
int pairableBetaCount = allBetas.size();
if(verbose){System.out.println("Remaining betas count: " + pairableBetaCount);}
if(verbose){System.out.println("Remaining alpha sequence count: " + alphaSequences.size());}
if(verbose){System.out.println("Remaining beta sequence count: " + betaSequences.size());}
if (readDepth > 1) {
if(verbose){System.out.println("Removing sequences with disparate occupancies and read counts");}
filterByOccupancyAndReadCount(alphaSequences, readDepth);
filterByOccupancyAndReadCount(betaSequences, readDepth);
if(verbose){System.out.println("Sequences removed");}
if(verbose){System.out.println("Remaining alpha sequence count: " + alphaSequences.size());}
if(verbose){System.out.println("Remaining beta sequence count: " + betaSequences.size());}
}
int pairableAlphaCount = alphaSequences.size();
if(verbose){System.out.println("Remaining alpha sequence count: " + pairableAlphaCount);}
int pairableBetaCount = betaSequences.size();
if(verbose){System.out.println("Remaining beta sequence count: " + pairableBetaCount);}
//construct the graph. For simplicity, going to make
if(verbose){System.out.println("Making vertex maps");}
//For the SimpleWeightedBipartiteGraphMatrixGenerator, all vertices must have
//distinct numbers associated with them. Since I'm using a 2D array, that means
//distinct indices between the rows and columns. vertexStartValue lets me track where I switch
//from numbering rows to columns, so I can assign unique numbers to every vertex, and then
//subtract the vertexStartValue from betas to use their vertex labels as array indices
Integer vertexStartValue = 0;
int vertexStartValue = 0;
//keys are sequential integer vertices, values are alphas
Map<Integer, Integer> plateVtoAMap = makeVertexToSequenceMap(allAlphas, vertexStartValue);
Map<String, Integer> plateAtoVMap = makeSequenceToVertexMap(alphaSequences, vertexStartValue);
//new start value for vertex to beta map should be one more than final vertex value in alpha map
vertexStartValue += plateVtoAMap.size();
//keys are sequential integers vertices, values are betas
Map<Integer, Integer> plateVtoBMap = makeVertexToSequenceMap(allBetas, vertexStartValue);
//keys are alphas, values are sequential integer vertices from previous map
Map<Integer, Integer> plateAtoVMap = invertVertexMap(plateVtoAMap);
//keys are betas, values are sequential integer vertices from previous map
Map<Integer, Integer> plateBtoVMap = invertVertexMap(plateVtoBMap);
vertexStartValue += plateAtoVMap.size();
//keys are betas, values are sequential integers
Map<String, Integer> plateBtoVMap = makeSequenceToVertexMap(betaSequences, vertexStartValue);
if(verbose){System.out.println("Vertex maps made");}
//make adjacency matrix for bipartite graph generator
//(technically this is only 1/4 of an adjacency matrix, but that's all you need
//for a bipartite graph, and all the SimpleWeightedBipartiteGraphMatrixGenerator class expects.)
if(verbose){System.out.println("Creating adjacency matrix");}
//Count how many wells each alpha appears in
Map<Integer, Integer> alphaWellCounts = new HashMap<>();
//count how many wells each beta appears in
Map<Integer, Integer> betaWellCounts = new HashMap<>();
//the adjacency matrix to be used by the graph generator
double[][] weights = new double[plateVtoAMap.size()][plateVtoBMap.size()];
countSequencesAndFillMatrix(samplePlate, allAlphas, allBetas, plateAtoVMap,
plateBtoVMap, alphaIndex, betaIndex, alphaWellCounts, betaWellCounts, weights);
if(verbose){System.out.println("Matrix created");}
//create bipartite graph
if(verbose){System.out.println("Creating graph");}
if(verbose){System.out.println("Making adjacency matrix");}
double[][] weights = new double[plateAtoVMap.size()][plateBtoVMap.size()];
fillAdjacencyMatrix(weights, vertexStartValue, alphaSequences, betaSequences, plateAtoVMap, plateBtoVMap);
if(verbose){System.out.println("Adjacency matrix made");}
//make bipartite graph
if(verbose){System.out.println("Making bipartite weighted graph");}
//the graph object
SimpleWeightedGraph<Integer, DefaultWeightedEdge> graph =
SimpleWeightedGraph<Vertex, DefaultWeightedEdge> graph =
new SimpleWeightedGraph<>(DefaultWeightedEdge.class);
//the graph generator
SimpleWeightedBipartiteGraphMatrixGenerator graphGenerator = new SimpleWeightedBipartiteGraphMatrixGenerator();
//the list of alpha vertices
List<Integer> alphaVertices = new ArrayList<>(plateVtoAMap.keySet()); //This will work because LinkedHashMap preserves order of entry
List<Vertex> alphaVertices = new ArrayList<>();
for (String seq : plateAtoVMap.keySet()) {
Vertex alphaVertex = new Vertex(alphaSequences.get(seq), plateAtoVMap.get(seq));
alphaVertices.add(alphaVertex);
}
//Sort to make sure the order of vertices in list matches the order of the adjacency matrix
Collections.sort(alphaVertices);
//Add ordered list of vertices to the graph
graphGenerator.first(alphaVertices);
//the list of beta vertices
List<Integer> betaVertices = new ArrayList<>(plateVtoBMap.keySet());
graphGenerator.second(betaVertices); //This will work because LinkedHashMap preserves order of entry
List<Vertex> betaVertices = new ArrayList<>();
for (String seq : plateBtoVMap.keySet()) {
Vertex betaVertex = new Vertex(betaSequences.get(seq), plateBtoVMap.get(seq));
betaVertices.add(betaVertex);
}
//Sort to make sure the order of vertices in list matches the order of the adjacency matrix
Collections.sort(betaVertices);
//Add ordered list of vertices to the graph
graphGenerator.second(betaVertices);
//use adjacency matrix of weight created previously
graphGenerator.weights(weights);
graphGenerator.generateGraph(graph);
if(verbose){System.out.println("Graph created");}
//stop timing
Instant stop = Instant.now();
Duration time = Duration.between(start, stop);
//create GraphWithMapData object
GraphWithMapData output = new GraphWithMapData(graph, numWells, samplePlate.getPopulations(), alphaCount, betaCount,
distCellsMapAlphaKey, plateVtoAMap, plateVtoBMap, plateAtoVMap,
plateBtoVMap, alphaWellCounts, betaWellCounts, time);
GraphWithMapData output = new GraphWithMapData(graph, numWells, samplePlate.getPopulations(), distCellsMapAlphaKey,
alphaCount, betaCount, readDepth, readErrorRate, errorCollisionRate, time);
//Set source file name in graph to name of sample plate
output.setSourceFilename(samplePlate.getSourceFileName());
output.setSourceFilename(samplePlate.getFilename());
//return GraphWithMapData object
return output;
}
@@ -145,47 +143,70 @@ public class Simulator {
Integer highThreshold, Integer maxOccupancyDifference,
Integer minOverlapPercent, boolean verbose) {
Instant start = Instant.now();
//Integer arrays will contain TO VERTEX, FROM VERTEX, and WEIGHT (which I'll need to cast to double)
List<Integer[]> removedEdges = new ArrayList<>();
SimpleWeightedGraph<Vertex, DefaultWeightedEdge> graph = data.getGraph();
Map<Vertex[], Integer> removedEdges = new HashMap<>();
boolean saveEdges = BiGpairSEQ.cacheGraph();
int numWells = data.getNumWells();
Integer alphaCount = data.getAlphaCount();
Integer betaCount = data.getBetaCount();
Map<Integer, Integer> distCellsMapAlphaKey = data.getDistCellsMapAlphaKey();
Map<Integer, Integer> plateVtoAMap = data.getPlateVtoAMap();
Map<Integer, Integer> plateVtoBMap = data.getPlateVtoBMap();
Map<Integer, Integer> alphaWellCounts = data.getAlphaWellCounts();
Map<Integer, Integer> betaWellCounts = data.getBetaWellCounts();
SimpleWeightedGraph<Integer, DefaultWeightedEdge> graph = data.getGraph();
//Integer alphaCount = data.getAlphaCount();
//Integer betaCount = data.getBetaCount();
Map<String, String> distCellsMapAlphaKey = data.getDistCellsMapAlphaKey();
Set<Vertex> alphas = new HashSet<>();
Set<Vertex> betas = new HashSet<>();
for(Vertex v: graph.vertexSet()) {
if (SequenceType.CDR3_ALPHA.equals(v.getType())){
alphas.add(v);
}
else {
betas.add(v);
}
}
Integer graphAlphaCount = alphas.size();
Integer graphBetaCount = betas.size();
//remove edges with weights outside given overlap thresholds, add those to removed edge list
if(verbose){System.out.println("Eliminating edges with weights outside overlap threshold values");}
removedEdges.addAll(GraphModificationFunctions.filterByOverlapThresholds(graph, lowThreshold, highThreshold));
removedEdges.putAll(GraphModificationFunctions.filterByOverlapThresholds(graph, lowThreshold, highThreshold, saveEdges));
if(verbose){System.out.println("Over- and under-weight edges removed");}
//remove edges between vertices with too small an overlap size, add those to removed edge list
if(verbose){System.out.println("Eliminating edges with weights less than " + minOverlapPercent.toString() +
" percent of vertex occupancy value.");}
removedEdges.addAll(GraphModificationFunctions.filterByOverlapPercent(graph, alphaWellCounts, betaWellCounts,
plateVtoAMap, plateVtoBMap, minOverlapPercent));
removedEdges.putAll(GraphModificationFunctions.filterByOverlapPercent(graph, minOverlapPercent, saveEdges));
if(verbose){System.out.println("Edges with weights too far below a vertex occupancy value removed");}
//Filter by relative occupancy
if(verbose){System.out.println("Eliminating edges between vertices with occupancy difference > "
+ maxOccupancyDifference);}
removedEdges.addAll(GraphModificationFunctions.filterByRelativeOccupancy(graph, alphaWellCounts, betaWellCounts,
plateVtoAMap, plateVtoBMap, maxOccupancyDifference));
removedEdges.putAll(GraphModificationFunctions.filterByRelativeOccupancy(graph, maxOccupancyDifference, saveEdges));
if(verbose){System.out.println("Edges between vertices of with excessively different occupancy values " +
"removed");}
//Find Maximum Weighted Matching
//Find Maximum Weight Matching
//using jheaps library class PairingHeap for improved efficiency
if(verbose){System.out.println("Finding maximum weighted matching");}
//Attempting to use addressable heap to improve performance
MaximumWeightBipartiteMatching maxWeightMatching =
new MaximumWeightBipartiteMatching(graph,
plateVtoAMap.keySet(),
plateVtoBMap.keySet(),
if(verbose){System.out.println("Finding maximum weight matching");}
MaximumWeightBipartiteMatching maxWeightMatching;
//Use correct heap type for priority queue
String heapType = BiGpairSEQ.getPriorityQueueHeapType();
switch (heapType) {
case "PAIRING" -> {
maxWeightMatching = new MaximumWeightBipartiteMatching(graph,
alphas,
betas,
i -> new PairingHeap(Comparator.naturalOrder()));
}
case "FIBONACCI" -> {
maxWeightMatching = new MaximumWeightBipartiteMatching(graph,
alphas,
betas,
i -> new FibonacciHeap(Comparator.naturalOrder()));
}
default -> {
maxWeightMatching = new MaximumWeightBipartiteMatching(graph,
alphas,
betas);
}
}
//get the matching
MatchingAlgorithm.Matching<String, DefaultWeightedEdge> graphMatching = maxWeightMatching.getMatching();
if(verbose){System.out.println("Matching completed");}
Instant stop = Instant.now();
@@ -209,14 +230,14 @@ public class Simulator {
int trueCount = 0;
int falseCount = 0;
boolean check;
Map<Integer, Integer> matchMap = new HashMap<>();
Map<String, String> matchMap = new HashMap<>();
while(weightIter.hasNext()) {
e = weightIter.next();
Integer source = graph.getEdgeSource(e);
Integer target = graph.getEdgeTarget(e);
Vertex source = graph.getEdgeSource(e);
Vertex target = graph.getEdgeTarget(e);
//The match map is all matches found, not just true matches!
matchMap.put(plateVtoAMap.get(source), plateVtoBMap.get(target));
check = plateVtoBMap.get(target).equals(distCellsMapAlphaKey.get(plateVtoAMap.get(source)));
matchMap.put(source.getSequence(), target.getSequence());
check = target.getSequence().equals(distCellsMapAlphaKey.get(source.getSequence()));
if(check) {
trueCount++;
}
@@ -224,33 +245,44 @@ public class Simulator {
falseCount++;
}
List<String> result = new ArrayList<>();
result.add(plateVtoAMap.get(source).toString());
//alpha sequence
result.add(source.getSequence());
//alpha well count
result.add(alphaWellCounts.get(plateVtoAMap.get(source)).toString());
result.add(plateVtoBMap.get(target).toString());
result.add(source.getOccupancy().toString());
//beta sequence
result.add(target.getSequence());
//beta well count
result.add(betaWellCounts.get(plateVtoBMap.get(target)).toString());
result.add(target.getOccupancy().toString());
//overlap count
result.add(Double.toString(graph.getEdgeWeight(e)));
result.add(Boolean.toString(check));
double pValue = Equations.pValue(numWells, alphaWellCounts.get(plateVtoAMap.get(source)),
betaWellCounts.get(plateVtoBMap.get(target)), graph.getEdgeWeight(e));
double pValue = Equations.pValue(numWells, source.getOccupancy(),
target.getOccupancy(), graph.getEdgeWeight(e));
BigDecimal pValueTrunc = new BigDecimal(pValue, mc);
result.add(pValueTrunc.toString());
allResults.add(result);
}
//Metadata comments for CSV file
int min = Math.min(alphaCount, betaCount);
String algoType = "LEDA book with heap: " + heapType;
int min = Math.min(graphAlphaCount, graphBetaCount);
//matching weight
BigDecimal totalMatchingWeight = maxWeightMatching.getMatchingWeight();
//rate of attempted matching
double attemptRate = (double) (trueCount + falseCount) / min;
BigDecimal attemptRateTrunc = new BigDecimal(attemptRate, mc);
//rate of pairing error
double pairingErrorRate = (double) falseCount / (trueCount + falseCount);
BigDecimal pairingErrorRateTrunc = new BigDecimal(pairingErrorRate, mc);
//get list of well concentrations
Integer[] wellPopulations = data.getWellConcentrations();
//make string out of concentrations list
BigDecimal pairingErrorRateTrunc;
if(Double.isFinite(pairingErrorRate)) {
pairingErrorRateTrunc = new BigDecimal(pairingErrorRate, mc);
}
else{
pairingErrorRateTrunc = new BigDecimal(-1, mc);
}
//get list of well populations
Integer[] wellPopulations = data.getWellPopulations();
//make string out of populations list
StringBuilder populationsStringBuilder = new StringBuilder();
populationsStringBuilder.append(wellPopulations[0].toString());
for(int i = 1; i < wellPopulations.length; i++){
@@ -258,37 +290,55 @@ public class Simulator {
populationsStringBuilder.append(wellPopulations[i].toString());
}
String wellPopulationsString = populationsStringBuilder.toString();
//graph generation time
Duration graphTime = data.getTime();
//MWM run time
Duration pairingTime = Duration.between(start, stop);
//total simulation time
Duration time = Duration.between(start, stop);
time = time.plus(data.getTime());
Duration totalTime = graphTime.plus(pairingTime);
Map<String, String> metadata = new LinkedHashMap<>();
metadata.put("sample plate filename", data.getSourceFilename());
metadata.put("graph filename", dataFilename);
metadata.put("MWM algorithm type", algoType);
metadata.put("matching weight", totalMatchingWeight.toString());
metadata.put("well populations", wellPopulationsString);
metadata.put("total alphas found", alphaCount.toString());
metadata.put("total betas found", betaCount.toString());
metadata.put("high overlap threshold", highThreshold.toString());
metadata.put("low overlap threshold", lowThreshold.toString());
metadata.put("maximum occupancy difference", maxOccupancyDifference.toString());
metadata.put("minimum overlap percent", minOverlapPercent.toString());
metadata.put("sequence read depth", data.getReadDepth().toString());
metadata.put("sequence read error rate", data.getReadErrorRate().toString());
metadata.put("read error collision rate", data.getErrorCollisionRate().toString());
metadata.put("total alphas read from plate", data.getAlphaCount().toString());
metadata.put("total betas read from plate", data.getBetaCount().toString());
//HARD CODED, PARAMETERIZE LATER
metadata.put("pre-filter sequences present in all wells", "true");
//HARD CODED, PARAMETERIZE LATER
metadata.put("pre-filter sequences based on occupancy/read count discrepancy", "true");
metadata.put("alphas in graph (after pre-filtering)", graphAlphaCount.toString());
metadata.put("betas in graph (after pre-filtering)", graphBetaCount.toString());
metadata.put("high overlap threshold for pairing", highThreshold.toString());
metadata.put("low overlap threshold for pairing", lowThreshold.toString());
metadata.put("minimum overlap percent for pairing", minOverlapPercent.toString());
metadata.put("maximum occupancy difference for pairing", maxOccupancyDifference.toString());
metadata.put("pairing attempt rate", attemptRateTrunc.toString());
metadata.put("correct pairing count", Integer.toString(trueCount));
metadata.put("incorrect pairing count", Integer.toString(falseCount));
metadata.put("pairing error rate", pairingErrorRateTrunc.toString());
metadata.put("simulation time", nf.format(time.toSeconds()));
metadata.put("time to generate graph (seconds)", nf.format(graphTime.toSeconds()));
metadata.put("time to pair sequences (seconds)",nf.format(pairingTime.toSeconds()));
metadata.put("total simulation time (seconds)", nf.format(totalTime.toSeconds()));
//create MatchingResult object
MatchingResult output = new MatchingResult(metadata, header, allResults, matchMap, time);
MatchingResult output = new MatchingResult(metadata, header, allResults, matchMap);
if(verbose){
for(String s: output.getComments()){
System.out.println(s);
}
}
//put the removed edges back on the graph
System.out.println("Restoring removed edges to graph.");
GraphModificationFunctions.addRemovedEdges(graph, removedEdges);
if(saveEdges) {
//put the removed edges back on the graph
System.out.println("Restoring removed edges to graph.");
GraphModificationFunctions.addRemovedEdges(graph, removedEdges);
}
//return MatchingResult object
return output;
}
@@ -599,81 +649,77 @@ public class Simulator {
// }
//Remove sequences based on occupancy
public static void filterByOccupancyThresholds(Map<Integer, Integer> wellMap, int low, int high){
List<Integer> noise = new ArrayList<>();
for(Integer k: wellMap.keySet()){
if((wellMap.get(k) > high) || (wellMap.get(k) < low)){
public static void filterByOccupancyThresholds(Map<String, SequenceRecord> wellMap, int low, int high){
List<String> noise = new ArrayList<>();
for(String k: wellMap.keySet()){
if((wellMap.get(k).getOccupancy() > high) || (wellMap.get(k).getOccupancy() < low)){
noise.add(k);
}
}
for(Integer k: noise) {
for(String k: noise) {
wellMap.remove(k);
}
}
//Counts the well occupancy of the row peptides and column peptides into given maps, and
//fills weights in the given 2D array
private static void countSequencesAndFillMatrix(Plate samplePlate,
Map<Integer,Integer> allRowSequences,
Map<Integer,Integer> allColumnSequences,
Map<Integer,Integer> rowSequenceToVertexMap,
Map<Integer,Integer> columnSequenceToVertexMap,
int[] rowSequenceIndices,
int[] colSequenceIndices,
Map<Integer, Integer> rowSequenceCounts,
Map<Integer,Integer> columnSequenceCounts,
double[][] weights){
Map<Integer, Integer> wellNRowSequences = null;
Map<Integer, Integer> wellNColumnSequences = null;
int vertexStartValue = rowSequenceToVertexMap.size();
int numWells = samplePlate.getSize();
for (int n = 0; n < numWells; n++) {
wellNRowSequences = samplePlate.assayWellsSequenceS(n, rowSequenceIndices);
for (Integer a : wellNRowSequences.keySet()) {
if(allRowSequences.containsKey(a)){
rowSequenceCounts.merge(a, 1, (oldValue, newValue) -> oldValue + newValue);
}
public static void filterByOccupancyAndReadCount(Map<String, SequenceRecord> sequences, int readDepth) {
List<String> noise = new ArrayList<>();
for(String k : sequences.keySet()){
//occupancy times read depth should be more than half the sequence read count if the read error rate is low
Integer threshold = (sequences.get(k).getOccupancy() * readDepth) / 2;
if(sequences.get(k).getReadCount() < threshold) {
noise.add(k);
}
wellNColumnSequences = samplePlate.assayWellsSequenceS(n, colSequenceIndices);
for (Integer b : wellNColumnSequences.keySet()) {
if(allColumnSequences.containsKey(b)){
columnSequenceCounts.merge(b, 1, (oldValue, newValue) -> oldValue + newValue);
}
}
for (Integer i : wellNRowSequences.keySet()) {
if(allRowSequences.containsKey(i)){
for (Integer j : wellNColumnSequences.keySet()) {
if(allColumnSequences.containsKey(j)){
weights[rowSequenceToVertexMap.get(i)][columnSequenceToVertexMap.get(j) - vertexStartValue] += 1.0;
}
}
}
}
}
for(String k : noise) {
sequences.remove(k);
}
}
private static Map<Integer, Integer> makeSequenceToSequenceMap(List<Integer[]> cells, int keySequenceIndex,
int valueSequenceIndex){
Map<Integer, Integer> keySequenceToValueSequenceMap = new HashMap<>();
for (Integer[] cell : cells) {
private static Map<String, String> makeSequenceToSequenceMap(List<String[]> cells, int keySequenceIndex,
int valueSequenceIndex){
Map<String, String> keySequenceToValueSequenceMap = new HashMap<>();
for (String[] cell : cells) {
keySequenceToValueSequenceMap.put(cell[keySequenceIndex], cell[valueSequenceIndex]);
}
return keySequenceToValueSequenceMap;
}
private static Map<Integer, Integer> makeVertexToSequenceMap(Map<Integer, Integer> sequences, Integer startValue) {
Map<Integer, Integer> map = new LinkedHashMap<>(); //LinkedHashMap to preserve order of entry
private static Map<Integer, String> makeVertexToSequenceMap(Map<String, SequenceRecord> sequences, Integer startValue) {
Map<Integer, String> map = new LinkedHashMap<>(); //LinkedHashMap to preserve order of entry
Integer index = startValue;
for (Integer k: sequences.keySet()) {
for (String k: sequences.keySet()) {
map.put(index, k);
index++;
}
return map;
}
private static Map<Integer, Integer> invertVertexMap(Map<Integer, Integer> map) {
Map<Integer, Integer> inverse = new HashMap<>();
private static Map<String, Integer> makeSequenceToVertexMap(Map<String, SequenceRecord> sequences, Integer startValue) {
Map<String, Integer> map = new LinkedHashMap<>(); //LinkedHashMap to preserve order of entry
Integer index = startValue;
for (String k: sequences.keySet()) {
map.put(k, index);
index++;
}
return map;
}
private static void fillAdjacencyMatrix(double[][] weights, Integer vertexOffsetValue, Map<String, SequenceRecord> rowSequences,
Map<String, SequenceRecord> columnSequences, Map<String, Integer> rowToVertexMap,
Map<String, Integer> columnToVertexMap) {
for (String rowSeq: rowSequences.keySet()) {
for (Integer well: rowSequences.get(rowSeq).getWells()) {
for (String colSeq: columnSequences.keySet()) {
if (columnSequences.get(colSeq).isInWell(well)) {
weights[rowToVertexMap.get(rowSeq)][columnToVertexMap.get(colSeq) - vertexOffsetValue] += 1.0;
}
}
}
}
}
private static Map<String, Integer> invertVertexMap(Map<Integer, String> map) {
Map<String, Integer> inverse = new HashMap<>();
for (Integer k : map.keySet()) {
inverse.put(map.get(k), k);
}

View File

@@ -1,17 +1,75 @@
public class Vertex {
private final Integer peptide;
private final Integer occupancy;
import org.jheaps.AddressableHeap;
public Vertex(Integer peptide, Integer occupancy) {
this.peptide = peptide;
this.occupancy = occupancy;
import java.io.Serializable;
import java.util.Map;
public class Vertex implements Serializable, Comparable<Vertex> {
private SequenceRecord record;
private Integer vertexLabel;
private Double potential;
private AddressableHeap queue;
public Vertex(SequenceRecord record, Integer vertexLabel) {
this.record = record;
this.vertexLabel = vertexLabel;
}
public Integer getPeptide() {
return peptide;
public SequenceRecord getRecord() { return record; }
public SequenceType getType() { return record.getSequenceType(); }
public Integer getVertexLabel() {
return vertexLabel;
}
public String getSequence() {
return record.getSequence();
}
public Integer getOccupancy() {
return occupancy;
return record.getOccupancy();
}
public Integer getReadCount() { return record.getReadCount(); }
public Map<Integer, Integer> getWellOccupancies() { return record.getWellOccupancies(); }
@Override //adapted from JGraphT example code
public int hashCode()
{
return (this.getSequence() == null) ? 0 : this.getSequence().hashCode();
}
@Override //adapted from JGraphT example code
public boolean equals(Object obj)
{
if (this == obj)
return true;
if (obj == null)
return false;
if (getClass() != obj.getClass())
return false;
Vertex other = (Vertex) obj;
if (this.getSequence() == null) {
return other.getSequence() == null;
} else {
return this.getSequence().equals(other.getSequence());
}
}
@Override //adapted from JGraphT example code
public String toString()
{
StringBuilder sb = new StringBuilder();
sb.append("(").append(vertexLabel)
.append(", Type: ").append(this.getType().name())
.append(", Sequence: ").append(this.getSequence())
.append(", Occupancy: ").append(this.getOccupancy()).append(")");
return sb.toString();
}
@Override
public int compareTo(Vertex other) {
return this.vertexLabel - other.getVertexLabel();
}
}