ArticleNAR genomics and bioinformatics2020
Poly-Enrich: count-based methods for gene set enrichment testing with genomic regions.
Article in NAR genomics and bioinformatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed, 26 citations in OpenAlex.
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- MUFFIN: a suite of tools for the analysis of functional sequencing data.NAR genomics and bioinformatics · 2024Article
- Genetic variation is a key determinant of chromatin accessibility and drives differences in the regulatory landscape of C57BL/6J and 129S1/SvImJ mice.Nucleic acids research · 2024Article
- An allosteric pan-TEAD inhibitor blocks oncogenic YAP/TAZ signaling and overcomes KRAS G12C inhibitor resistance.Nature cancer · 2023Article
- Perinatal Lead Exposure Promotes Sex-Specific Epigenetic Programming of Disease-Relevant Pathways in Mouse Heart.Toxics · 2023Article
- Nine quick tips for pathway enrichment analysis.PLoS computational biology · 2022Article
- Comprehensive enhancer-target gene assignments improve gene set level interpretation of genome-wide regulatory data.Genome biology · 2022Article
- A brief survey of tools for genomic regions enrichment analysis.Frontiers in bioinformatics · 2022Review
- Tissue and sex-specific programming of DNA methylation by perinatal lead exposure: implications for environmental epigenetics studies.Epigenetics · 2021Article
- Sex-Specific Alterations in Cardiac DNA Methylation in Adult Mice by Perinatal Lead Exposure.International journal of environmental research and public health · 2021Article
- Testing Proximity of Genomic Regions to Transcription Start Sites and Enhancers Complements Gene Set Enrichment Testing.Frontiers in genetics · 2020Article
- Sex-Specific Programming of Cardiac DNA Methylation by Developmental Phthalate Exposure.Epigenetics insights · 2020Article
Corrections and comments
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Authors and funding
9 authors at 1 institution in 1 country.
Funding
Abstract
Gene set enrichment (GSE) testing enhances the biological interpretation of ChIP-seq data and other large sets of genomic regions. Our group has previously introduced two GSE methods for genomic regions: ChIP-Enrich for narrow regions and Broad-Enrich for broad regions. Here, we introduce Poly-Enrich, which has wider applicability, additional capabilities and models the number of peaks assigned to a gene using a generalized additive model with a negative binomial family to determine gene set enrichment, while adjusting for gene locus length. As opposed to ChIP-Enrich, Poly-Enrich works well even when nearly all genes have a peak, illustrated by using Poly-Enrich to characterize pathways and types of genic regions enriched with different families of repetitive elements. By comparing Poly-Enrich and ChIP-Enrich results with ENCODE ChIP-seq data, we found that the optimal test depends more on the pathway being regulated than on properties of the transcription factors. Using known transcription factor functions, we discovered clusters of related biological processes consistently better modeled with Poly-Enrich. This suggests that the regulation of certain processes may be modified by multiple binding events, better modeled by a count-based method. Our new hybrid method automatically uses the optimal method for each gene set, with correct FDR-adjustment.
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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.