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.
Hossain et al. (2026) studied this question.