mitch: multi-contrast pathway enrichment for multi-omics and single-cell profiling data
Abstract 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 ava...
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doaj-0faf66a9992a4bd4a97218b4fe869aa02020-11-25T02:50:13ZengBMCBMC Genomics1471-21642020-06-0121111710.1186/s12864-020-06856-9mitch: multi-contrast pathway enrichment for multi-omics and single-cell profiling dataAntony Kaspi0Mark Ziemann1Population Health and Immunity Division, The Walter and Eliza Hall Institute of Medical ResearchSchool of Life and Environmental Sciences, Deakin UniversityAbstract 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 ( https://bioconductor.org/packages/mitch ).http://link.springer.com/article/10.1186/s12864-020-06856-9Bioconductor packageDifferential expressionGene regulationMulti-omicsSingle-cell profilingPathway analysis |
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DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Antony Kaspi Mark Ziemann |
spellingShingle |
Antony Kaspi Mark Ziemann mitch: multi-contrast pathway enrichment for multi-omics and single-cell profiling data BMC Genomics Bioconductor package Differential expression Gene regulation Multi-omics Single-cell profiling Pathway analysis |
author_facet |
Antony Kaspi Mark Ziemann |
author_sort |
Antony Kaspi |
title |
mitch: multi-contrast pathway enrichment for multi-omics and single-cell profiling data |
title_short |
mitch: multi-contrast pathway enrichment for multi-omics and single-cell profiling data |
title_full |
mitch: multi-contrast pathway enrichment for multi-omics and single-cell profiling data |
title_fullStr |
mitch: multi-contrast pathway enrichment for multi-omics and single-cell profiling data |
title_full_unstemmed |
mitch: multi-contrast pathway enrichment for multi-omics and single-cell profiling data |
title_sort |
mitch: multi-contrast pathway enrichment for multi-omics and single-cell profiling data |
publisher |
BMC |
series |
BMC Genomics |
issn |
1471-2164 |
publishDate |
2020-06-01 |
description |
Abstract 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 ( https://bioconductor.org/packages/mitch ). |
topic |
Bioconductor package Differential expression Gene regulation Multi-omics Single-cell profiling Pathway analysis |
url |
http://link.springer.com/article/10.1186/s12864-020-06856-9 |
work_keys_str_mv |
AT antonykaspi mitchmulticontrastpathwayenrichmentformultiomicsandsinglecellprofilingdata AT markziemann mitchmulticontrastpathwayenrichmentformultiomicsandsinglecellprofilingdata |
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