ArticleNucleic acids research2021
Integrative analysis of epigenetics data identifies gene-specific regulatory elements.
Article in Nucleic acids research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed, 30 citations in OpenAlex.
- Comparing machine learning methods predicting transcriptome from epigenome with applications to association studies.Genome biology · 2026Article
- Predicting gene-specific regulation with transcriptomic and epigenetic single-cell data.Bioinformatics (Oxford, England) · 2026Article
- Atlas of nascent RNA transcripts reveals tissue-specific enhancer to gene linkages.BMC genomics · 2025Article
- Prediction of Enhancer-Gene Interactions Using Chromatin-Conformation Capture and Epigenome Data Using STARE.Methods in molecular biology (Clifton, N.J.) · 2025Article
- Learning Enhancer-Gene associations from Bulk Transcriptomic and Epigenetic Sequencing Data with STITCHIT.Methods in molecular biology (Clifton, N.J.) · 2025Article
- A statistical approach for identifying single nucleotide variants that affect transcription factor binding.iScience · 2024Article
- Churros: a Docker-based pipeline for large-scale epigenomic analysis.DNA research : an international journal for rapid publication of reports on genes and genomes · 2024Article
- IVEA: an integrative variational Bayesian inference method for predicting enhancer-gene regulatory interactions.Bioinformatics advances · 2024Article
- CVD-associated SNPs with regulatory potential reveal novel non-coding disease genes.Human genomics · 2023Article
- MYB insufficiency disrupts proteostasis in hematopoietic stem cells, leading to age-related neoplasia.Blood · 2023Article
- The adapted Activity-By-Contact model for enhancer-gene assignment and its application to single-cell data.Bioinformatics (Oxford, England) · 2023Article
- De novo annotation of lncRNA HOTAIR transcripts by long-read RNA capture-seq reveals a differentiation-driven isoform switch.BMC genomics · 2022Article
- Pioneer transcription factors are associated with the modulation of DNA methylation patterns across cancers.Epigenetics & chromatin · 2022Article
- Chromatin occupancy and target genes of the haematopoietic master transcription factor MYB.Scientific reports · 2021Article
- EpiRegio: analysis and retrieval of regulatory elements linked to genes.Nucleic acids research · 2020Article
- Integrative prediction of gene expression with chromatin accessibility and conformation data.Epigenetics & chromatin · 2020Article
Corrections and comments
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Authors and funding
11 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Understanding how epigenetic variation in non-coding regions is involved in distal gene-expression regulation is an important problem. Regulatory regions can be associated to genes using large-scale datasets of epigenetic and expression data. However, for regions of complex epigenomic signals and enhancers that regulate many genes, it is difficult to understand these associations. We present StitchIt, an approach to dissect epigenetic variation in a gene-specific manner for the detection of regulatory elements (REMs) without relying on peak calls in individual samples. StitchIt segments epigenetic signal tracks over many samples to generate the location and the target genes of a REM simultaneously. We show that this approach leads to a more accurate and refined REM detection compared to standard methods even on heterogeneous datasets, which are challenging to model. Also, StitchIt REMs are highly enriched in experimentally determined chromatin interactions and expression quantitative trait loci. We validated several newly predicted REMs using CRISPR-Cas9 experiments, thereby demonstrating the reliability of StitchIt. StitchIt is able to dissect regulation in superenhancers and predicts thousands of putative REMs that go unnoticed using peak-based approaches suggesting that a large part of the regulome might be uncharted water.
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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.