Rename and update readme
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@@ -55,6 +55,7 @@ public class Plate {
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List<Integer[]> well = new ArrayList<>();
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for (int j = 0; j < concentrations[section]; j++) {
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do {
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//inverse transform sampling: for random number u in [0,1), x = log(1-u) / (-lambda)
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m = (Math.log10((1 - rand.nextDouble()))/(-lambda)) * Math.sqrt(cells.size());
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} while (m >= cells.size() || m < 0);
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n = (int) Math.floor(m);
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@@ -269,7 +269,7 @@ public class UserInterface {
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//Need to re-do the CDR3/CDR1 matching to correspond to new pattern
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//System.out.println("5) Generate CDR3/CDR1 occupancy graph");
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//System.out.println("6) Simulate CDR3/CDR1 T cell matching");
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System.out.println("9) Acknowledgements");
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System.out.println("9) About/Acknowledgments");
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System.out.println("0) Exit");
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try {
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input = sc.nextInt();
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@@ -384,8 +384,8 @@ public class UserInterface {
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System.out.println("1) Poisson");
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System.out.println("2) Gaussian");
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System.out.println("3) Exponential");
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System.out.println("(Note: approximate distribution in original paper is exponential, lambda = 0.6.)");
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System.out.println("(approximated from slope of log-log graph in figure 4c)");
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System.out.println("(Note: approximate distribution in original paper is exponential, lambda = 0.6)");
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System.out.println("(lambda value approximated from slope of log-log graph in figure 4c)");
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System.out.println("(Note: wider distributions are more memory intensive to match)");
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System.out.print("Enter selection value: ");
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input = sc.nextInt();
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@@ -664,6 +664,17 @@ public class UserInterface {
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System.out.println("This program simulates BiGpairSEQ, a graph theory based adaptation");
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System.out.println("of the pairSEQ algorithm for pairing T cell receptor sequences.");
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System.out.println("");
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System.out.println("Unlike pairSEQ, which calculates p-values for every TCR alpha/beta overlap and compares");
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System.out.println("against a null distribution, BiGpairSEQ does not do any statistical calculations");
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System.out.println("directly. Instead, BiGpairSEQ creates a simple bipartite weighted graph representing");
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System.out.println("the sample plate. The distinct TCRA and TCRB sequences form the two sets of vertices.");
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System.out.println("Every TCRA/TCRB pair that share a well are connected by an edge, with the edge weight");
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System.out.println("set to the number of wells in which both sequences appear. (Sequences in all wells are");
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System.out.println("filtered out prior to creating the graph, as there is no signal in their occupancy");
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System.out.println("pattern.) The problem of pairing TCRA/TCRB sequences thus reduces to the \"assignment");
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System.out.println("problem\" of finding a maximum weight matching on a bipartite graph--the subset of");
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System.out.println("vertex-disjoint edges whose weights sum to the maximum possible value.");
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System.out.println("");
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System.out.println("pairSEQ citation:");
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System.out.println("Howie, B., Sherwood, A. M., et. al.");
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System.out.println("High-throughput pairing of T cell receptor alpha and beta sequences.");
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