ArticleNucleic acids research2019
HMMRATAC: a Hidden Markov ModeleR for ATAC-seq.
Article in Nucleic acids research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 63 papers.
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Who cites it
63 citing papers in PubMed.
- Robust regulatory interplay of enhancers, facilitators, and promoters in a native chromatin context.Cell · 2026Article
- Integrative Epigenomics: Bioinformatics Strategies for Multi-Omics Data Analysis in Health and Disease.Epigenomes · 2026Review
- Article
- An inducible system to study the regulatory functions of GSX2 in human lateral ganglionic eminence-like progenitors.Developmental biology · 2026Article
- Three-dimensional genome reorganization foreshadows zygotic genome activation in Drosophila.Nature genetics · 2026Article
- Method for ATAC Sequencing Data Analysis for Understanding Chromatin Biology in Legumes.Methods in molecular biology (Clifton, N.J.) · 2026Article
- Computational Analyses and Challenges of Single-cell ATAC-seq.Genomics, proteomics & bioinformatics · 2025Review
- AP1 is a pioneer transcription factor that programmes cell fate through MADS-domain protein tetramerisation.Genome biology · 2025Article
- HIRA defines early replication initiation zones independently of their genome compartment.Nature communications · 2025Article
- ATAC-seq in Emerging Model Organisms: Challenges and Strategies.Journal of experimental zoology. Part B, Molecular and developmental evolution · 2025Review
- Genetic integration with cell-specific nucleosome positioning resolves causal relationships underlying chromatin accessibility profiles.bioRxiv : the preprint server for biology · 2025Article
- Article
- Transcriptomic landscape and chromatin accessibility uncover pivotal regulators driving programmed larval-larval molting in the domesticated silkworm.PLoS genetics · 2025Article
- Chromatin accessibility provides a window into the genetic etiology of human brain disease.Trends in genetics : TIG · 2025Review
- Copy number normalization distinguishes differential signals driven by copy number differences in ATAC-seq and ChIP-seq.BMC genomics · 2025Article
- Genetic coupling of enhancer activity and connectivity in gene expression control.Nature communications · 2025Article
- Heterochromatic gene silencing controls CD4Nature communications · 2025Article
- Integrative multiomics reveals common endotypes across PSEN1, PSEN2, and APP mutations in familial Alzheimer's disease.Alzheimer's research & therapy · 2025Article
- Cut&tag: a powerful epigenetic tool for chromatin profiling.Epigenetics · 2024Review
- Review
3 more citing papers are in PubMed but not listed here.
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Authors and funding
2 authors.
Funding
Abstract
ATAC-seq has been widely adopted to identify accessible chromatin regions across the genome. However, current data analysis still utilizes approaches initially designed for ChIP-seq or DNase-seq, without considering the transposase digested DNA fragments that contain additional nucleosome positioning information. We present the first dedicated ATAC-seq analysis tool, a semi-supervised machine learning approach named HMMRATAC. HMMRATAC splits a single ATAC-seq dataset into nucleosome-free and nucleosome-enriched signals, learns the unique chromatin structure around accessible regions, and then predicts accessible regions across the entire genome. We show that HMMRATAC outperforms the popular peak-calling algorithms on published human ATAC-seq datasets. We find that single-end sequenced or size-selected ATAC-seq datasets result in a loss of sensitivity compared to paired-end datasets without size-selection.
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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.