mitch: multi-contrast pathway enrichment for multi-omics and single-cell profiling data

BMC Genomics. 2020 Jun 29;21(1):447. doi: 10.1186/s12864-020-06856-9.


Background: Inference of biological pathway activity via gene set enrichment analysis is frequently used in the interpretation of clinical and other omics data. With the proliferation of new omics profiling approaches and ever-growing size of data sets generated, there is a lack of tools available to perform and visualise gene set enrichments in analyses involving multiple contrasts.

Results: To address this, we developed mitch, an R package for multi-contrast gene set enrichment analysis. It uses a rank-MANOVA statistical approach to identify sets of genes that exhibit joint enrichment across multiple contrasts. Its unique visualisation features enable the exploration of enrichments in up to 20 contrasts. We demonstrate the utility of mitch with case studies spanning multi-contrast RNA expression profiling, integrative multi-omics, tool benchmarking and single-cell RNA sequencing. Using simulated data we show that mitch has similar accuracy to state of the art tools for single-contrast enrichment analysis, and superior accuracy in identifying multi-contrast enrichments.

Conclusion: mitch is a versatile tool for rapidly and accurately identifying and visualising gene set enrichments in multi-contrast omics data. Mitch is available from Bioconductor ( ).

Keywords: Bioconductor package; Differential expression; Gene regulation; Gene set enrichment analysis; Multi-omics; Multivariate statistics; Pathway analysis; Single-cell profiling.

MeSH terms

  • Computational Biology / methods*
  • Gene Expression Profiling
  • Gene Regulatory Networks
  • Humans
  • Sequence Analysis, RNA
  • Single-Cell Analysis / methods*
  • Software