An R/C++ package to identify patterns and biological process activity in transcriptomic data. CoGAPS provides an integrated package for isolating gene expression driven by a biological process, enhancing inference of biological processes from transcriptomic data. It improves on other enrichment measurement methods by combining a Markov chain Monte Carlo (MCMC) matrix factorization algorithm (GAPS) with a threshold-independent statistic inferring activity on gene sets. coGAPS infers biological activity by identifying overlapping, coregulated sets of genes and applying Z-score based statistics. It can be used to isolate transcription factor (TF) or BP activity in datasets of thousands of genes and tens to thousands of samples. The software is provided as open source C++ code built on top of JAGS software with an R interface.