The rankSynergy performs a rank-based non-parametric statistical test for measuring the synergistic effects between two gene sets. For calculating an approximate significance value of synergy, an efficient Markov chain Monte Carlo method is used. This software is a C++ implementation of the algorithm proposed in the paper below.
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"A rank-based statistical test for measuring synergistic effects between two gene sets", Shiraishi et al., Bioinformatics, 2011.
Two input files representing ranked genes (e.g., according to expression values) with indicator value (1: included in the gene set, 0: otherwise) are necessary. For example, the following file
1
0
0
1
1
0
1
0
0
shows that the 1st, 4th, 5th and 7th are included in the specific gene set among 10 ranked genes. Please check the E2F_rank.txt and NFY_rank.txt files, which show whether each gene has E2F and NFY motifs, respectively, in its promoter sequence.
Please note that the two input file are ranked by the same criterion. Therefore, for example, the 100th genes in the first and second input files should be the same gene.
We recommend that the ratio of genes included in gene sets do not exceed 50%.
Compile C++ programs
$ make
Just type the following command
$ rankSynergy <the first input file> <the second input file> <the output file> <the number of MCMC cycles (optional)> <the number of burn-in cycles (optional)>
Then you will get the result in the output file under the specified output directory.
Type the following command after compiling.
rankSynergy E2F_rank.txt NFY_rank.txt output.txt 10000000 100000
Then, you will get the result in the "output.txt".