ArticleBMC genomics2018
ATAC2GRN: optimized ATAC-seq and DNase1-seq pipelines for rapid and accurate genome regulatory network inference.
Article in BMC genomics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 20 papers.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
20 citing papers in PubMed.
- Genome-wide nucleosome and transcription factor responses to genetic perturbations reveal chromatin-mediated mechanisms of transcriptional regulation.Genome research · 2026Article
- ATAC-seq in Emerging Model Organisms: Challenges and Strategies.Journal of experimental zoology. Part B, Molecular and developmental evolution · 2025Review
- OneSC: a computational platform for recapitulating cell state transitions.Bioinformatics (Oxford, England) · 2024Article
- OneSC: A computational platform for recapitulating cell state transitions.bioRxiv : the preprint server for biology · 2024Article
- Emerging Approaches to Profile Accessible Chromatin from Formalin-Fixed Paraffin-Embedded Sections.Epigenomes · 2024Review
- Recent advances in exploring transcriptional regulatory landscape of crops.Frontiers in plant science · 2024Review
- Article
- A network of transcription factors governs the dynamics of NODAL/Activin transcriptional responses.Journal of cell science · 2022Article
- Epigenetic Regulation of Endothelial Cell Lineages During Zebrafish Development-New Insights From Technical Advances.Frontiers in cell and developmental biology · 2022Review
- PEPATAC: an optimized pipeline for ATAC-seq data analysis with serial alignments.NAR genomics and bioinformatics · 2021Article
- Towards improved genetic diagnosis of human differences of sex development.Nature reviews. Genetics · 2021Review
- AIAP: A Quality Control and Integrative Analysis Package to Improve ATAC-seq Data Analysis.Genomics, proteomics & bioinformatics · 2021Article
- Computational systems-biology approaches for modeling gene networks driving epithelial-mesenchymal transitions.Computational and systems oncology · 2021Article
- Analytical Approaches for ATAC-seq Data Analysis.Current protocols in human genetics · 2020Article
- ATAC-seq normalization method can significantly affect differential accessibility analysis and interpretation.Epigenetics & chromatin · 2020Article
- From reads to insight: a hitchhiker's guide to ATAC-seq data analysis.Genome biology · 2020Review
- XL-DNase-seq: improved footprinting of dynamic transcription factors.Epigenetics & chromatin · 2019Article
- Integrated Epigenetic Mapping of Human and Mouse Salivary Gene Regulation.Journal of dental research · 2019Article
- Correction to: ATAC2GRN: optimized ATAC-seq and DNase1-seq pipelines for rapid and accurate genome regulatory network inference.BMC genomics · 2019Article
- Review
Corrections and comments
- Erratum issued
Authors and funding
3 authors.
Funding
Abstract
backgroundChromatin accessibility profiling assays such as ATAC-seq and DNase1-seq offer the opportunity to rapidly characterize the regulatory state of the genome at a single nucleotide resolution. Optimization of molecular protocols has enabled the molecular biologist to produce next-generation sequencing libraries in several hours, leaving the analysis of sequencing data as the primary obstacle to wide-scale deployment of accessibility profiling assays. To address this obstacle we have developed an optimized and efficient pipeline for the analysis of ATAC-seq and DNase1-seq data.
resultsWe executed a multi-dimensional grid-search on the NIH Biowulf supercomputing cluster to assess the impact of parameter selection on biological reproducibility and ChIP-seq recovery by analyzing 4560 pipeline configurations. Our analysis improved ChIP-seq recovery by 15% for ATAC-seq and 3% for DNase1-seq and determined that PCR duplicate removal improves biological reproducibility by 36% without significant costs in footprinting transcription factors. Our analyses of down sampled reads identified a point of diminishing returns for increased library sequencing depth, with 95% of the ChIP-seq data of a 200 million read footprinting library recovered by 160 million reads.
conclusionsWe present optimized ATAC-seq and DNase-seq pipelines in both Snakemake and bash formats as well as optimal sequencing depths for ATAC-seq and DNase-seq projects. The optimized ATAC-seq and DNase1-seq analysis pipelines, parameters, and ground-truth ChIP-seq datasets have been made available for deployment and future algorithmic profiling.
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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.