ArticleBMC genomics2020
mitch: multi-contrast pathway enrichment for multi-omics and single-cell profiling data.
Article in BMC genomics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers, 3 of them syntheses that pooled it.
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Who cites it
44 citing papers in PubMed, 3 syntheses or guidelines pooled it, 64 citations in OpenAlex.
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- Meta-analysis of DNA methylation aging signatures in 17 human tissues.Nature aging · 2026Pooled it
- Exercise is associated with younger methylome and transcriptome profiles in human skeletal muscle.Aging cell · 2024Pooled it
- Sprint interval exercise disrupts mitochondrial ultrastructure driving a unique mitochondrial stress response and remodelling in men.Nature communications · 2025Trial
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- Metabolic pathways fuelling devil facial tumour diseases.The FEBS journal · 2026Article
- A multi-omics analysis of human fibroblasts overexpressing an Alu transposon reveals widespread disruptions in aging-associated pathways.GeroScience · 2026Article
- Continuous multi-omics pathway enrichment analysis resolves hidden functional heterogeneity.Briefings in bioinformatics · 2026Article
- A multi-omic atlas in the African turquoise killifish reveals increased glucocorticoid signaling as a hallmark of brain aging.bioRxiv : the preprint server for biology · 2026Article
- Ten common mistakes that could ruin your enrichment analysis.PLoS computational biology · 2026Article
- The transcriptomic signature of age and sex is not conserved in human primary myotubes.Skeletal muscle · 2026Article
- FUNCellA: A Tool for Single-Sample Enrichment Analysis and Relative Pathway Activity Estimation in Single-Cell RNA Sequencing Data.Computational and structural biotechnology journal · 2026Article
- Systematic evaluation of CrRNA design parameters for optimized Cas13d-mediated RNA targeting in chicken cells.Functional & integrative genomics · 2025Article
- Acidic melanoma microenvironment selects for a senescence-like but also migratory-active subpopulation driving metastatic disease.Cell death discovery · 2025Article
- A multi-omics analysis of human fibroblasts overexpressing anbioRxiv : the preprint server for biology · 2025Article
- Deep phenotyping of a modified diabetic cardiomyopathy mouse model which reflects clinical disease progression.Diabetology & metabolic syndrome · 2025Article
- Gene expression correlates and mechanistic insights into electric organ discharge duration changes in mormyrid electric fish.The Journal of experimental biology · 2025Article
- 5G-exposed human skin cells do not respond with altered gene expression and methylation profiles.PNAS nexus · 2025Article
- Loosening the Lid on Shoulder Osteoarthritis: How the Transcriptome and Metabolic Syndrome Correlate with End-Stage Disease.International journal of molecular sciences · 2025Article
- Integrative multiomics reveals common endotypes across PSEN1, PSEN2, and APP mutations in familial Alzheimer's disease.Alzheimer's research & therapy · 2025Article
Corrections and comments
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Authors and funding
2 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundInference 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.
resultsTo 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.
conclusionmitch is a versatile tool for rapidly and accurately identifying and visualising gene set enrichments in multi-contrast omics data. Mitch is available from Bioconductor ( https://bioconductor.org/packages/mitch ).
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.