Rank-rank hypergeometric overlap: identification of statistically significant overlap between gene-expression signatures.

ABSTRACT: Comparing independent high-throughput gene-expression experiments can generate hypotheses about which gene-expression programs are shared between particular biological processes. Current techniques to compare expression profiles typically involve choosing a fixed differential expression threshold to summarize results, potentially reducing sensitivity to small but concordant changes. We present a threshold-free algorithm called Rank-rank Hypergeometric Overlap (RRHO). This algorithm steps through two gene lists ranked by the degree of differential expression observed in two profiling experiments, successively measuring the statistical significance of the number of overlapping genes. The output is a graphical map that shows the strength, pattern and bounds of correlation between two expressi

SUBMITTER: Plaisier SB 

PROVIDER: S-EPMC2943622 | biostudies-literature | 2010 Sep

REPOSITORIES: biostudies-literature