ChromAcS: an automated and flexible GUI for end-to-end reproducible ATAC-seq analysis across multiple species

Chromatin accessibility profiling is central for understanding gene regulation, yet ATAC-seq data analysis remains computationally challenging due to its multistep complexity. Here, we introduce ChromAcS, a versatile GUI-based, end-to-end integrated pipeline for streamlined and reproducible analysis of paired-end ATAC-seq data. Utilizing state-of-the-art methods, ChromAcS performs automated quality control, adapter trimming, read alignment, coverage track generation, peak calling, genomic peak annotation, differential accessibility analysis (supporting both replicate-aware and replicate-free designs), motif enrichment and regulatory network analysis, and motif footprinting over differential conditions. It also enables multi-omic exploration through genomic coordinate-based integration with other epigenomic datasets and identifier-specific integration with gene expression datasets. The pipeline allows user-defined choices at key steps. It supports flexible parameter optimization, multi-species genome selection, real-time progress monitoring, and modularity. Designed to run locally, ChromAcS minimizes setup friction while maximizing analytical depth. We benchmark ChromAcS using public datasets, demonstrating its reproducibility and the impact of user-defined thresholds and design choices on biological interpretation. By combining accessibility with state-of-the-art analytical tools, ChromAcS empowers a broader scientific community to generate high-quality insights from ATAC-seq data, accelerating chromatin biology research in both bulk and context-specific applications. Tool available at: https://github.com/epigen-bioinfolab/CHROMACS. ChromAcS is a comprehensive open-source, GUI-based ATAC-seq analysis pipeline supporting multi-species genomes with real-time progress monitoring and modular re-execution. It integrates state-of-the-art tools for quality control, alignment, peak calling, annotation, differential accessibility, motif enrichment, and footprinting into a reproducible end-to-end workflow. ChromAcS provides flexible parameter optimization and choice of algorithms (e.g., Genrich vs. MACS3, DiffBind vs. NOISeq), enabling users to benchmark sensitivity/specificity tradeoffs without extensive coding. The pipeline empowers non-computational biologists by minimizing setup friction, while retaining analytical depth suitable for advanced epigenomic studies. ChromAcS facilitates multi-omic exploration through genomic coordinate-based integration with other epigenomic datasets (e.g., ChIP-seq) and identifier-specific integration with gene expression data (e.g., RNA-seq), to accelerate chromatin biology research in broader contexts.

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Publication Details

Journal
BMC Bioinformatics
Published
2026-02-04
DOI
https://doi.org/10.1186/s12859-026-06382-7
Primary Topic
Genomics and Chromatin Dynamics
Type
article
Field-Weighted Citation Impact
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article

ChromAcS: an automated and flexible GUI for end-to-end reproducible ATAC-seq analysis across multiple species

Abul Bashar Mir Md. Khademul Islam, Muhaiminur Hossain, Anik Mojumder, S M Mahbubur Rashid
BMC Bioinformatics
Genomics and Chromatin Dynamics
article

ChromAcS: an automated and flexible GUI for end-to-end reproducible ATAC-seq analysis across multiple species

Abul Bashar Mir Md. Khademul Islam, Muhaiminur Hossain, Anik Mojumder, S M Mahbubur Rashid
article en

Abstract

Chromatin accessibility profiling is central for understanding gene regulation, yet ATAC-seq data analysis remains computationally challenging due to its multistep complexity. Here, we introduce ChromAcS, a versatile GUI-based, end-to-end integrated pipeline for streamlined and reproducible analysis of paired-end ATAC-seq data. Utilizing state-of-the-art methods, ChromAcS performs automated quality control, adapter trimming, read alignment, coverage track generation, peak calling, genomic peak annotation, differential accessibility analysis (supporting both replicate-aware and replicate-free designs), motif enrichment and regulatory network analysis, and motif footprinting over differential conditions. It also enables multi-omic exploration through genomic coordinate-based integration with other epigenomic datasets and identifier-specific integration with gene expression datasets. The pipeline allows user-defined choices at key steps. It supports flexible parameter optimization, multi-species genome selection, real-time progress monitoring, and modularity. Designed to run locally, ChromAcS minimizes setup friction while maximizing analytical depth. We benchmark ChromAcS using public datasets, demonstrating its reproducibility and the impact of user-defined thresholds and design choices on biological interpretation. By combining accessibility with state-of-the-art analytical tools, ChromAcS empowers a broader scientific community to generate high-quality insights from ATAC-seq data, accelerating chromatin biology research in both bulk and context-specific applications. Tool available at: https://github.com/epigen-bioinfolab/CHROMACS. ChromAcS is a comprehensive open-source, GUI-based ATAC-seq analysis pipeline supporting multi-species genomes with real-time progress monitoring and modular re-execution. It integrates state-of-the-art tools for quality control, alignment, peak calling, annotation, differential accessibility, motif enrichment, and footprinting into a reproducible end-to-end workflow. ChromAcS provides flexible parameter optimization and choice of algorithms (e.g., Genrich vs. MACS3, DiffBind vs. NOISeq), enabling users to benchmark sensitivity/specificity tradeoffs without extensive coding. The pipeline empowers non-computational biologists by minimizing setup friction, while retaining analytical depth suitable for advanced epigenomic studies. ChromAcS facilitates multi-omic exploration through genomic coordinate-based integration with other epigenomic datasets (e.g., ChIP-seq) and identifier-specific integration with gene expression data (e.g., RNA-seq), to accelerate chromatin biology research in broader contexts.

BMC BioinformaticsVol. 27(1)
University of Dhaka (BD)
Openalex Percentile: Top 67%
Genomics and Chromatin Dynamics
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