2 Commits

Author SHA1 Message Date
7f18311054 fix typos 2022-02-24 15:55:32 -06:00
bcb816c3e6 Reformat TODO 2022-02-24 15:48:10 -06:00

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@@ -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 against a null distribution, BiGpairSEQ does not do any statistical calculations
directly. directly.
BiGpairSEQ creates a [weightd bipartite 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 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. 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.) (Sequences present in *all* wells are filtered out prior to creating the graph, as there is no signal in their occupancy pattern.)
@@ -254,7 +254,7 @@ slightly less time than the simulation itself. Real elapsed time from start to f
## TODO ## TODO
* ~~Try invoking GC at end of workloads to reduce paging to disk~~ DONE * ~~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.*~~ * ~~*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. * 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 is possible, though the modifications to the graph incur their own performance penalties. Need testing to see which option is best.