esATAC
esATAC provides integrated analysis of ATAC-seq data for genome-wide characterization of chromatin accessibility and downstream regulatory analyses.
Key Features:
- Integrated workflow: Performs end-to-end ATAC-seq analyses including quality control, peak calling, enrichment analysis, and transcription factor footprinting.
- Raw data processing: Preprocesses FASTQ files for downstream analysis.
- Reads alignment and formats: Supports alignment via Rbowtie2 and operations on aligned reads in SAM, BAM, and BED formats.
- Peak calling: Implements peak calling with F-seq to identify regions of open chromatin.
- Genome annotation and downstream analyses: Facilitates motif discovery, Gene Ontology (GO) analysis, and SNP analysis.
- Quality control: Generates quality control reports to assess data reliability.
- Statistical and enrichment analysis: Includes advanced statistical analyses and enrichment analysis for regulatory interpretation.
- Implementation: Provided as an R/Bioconductor package with implementations in R and C++.
Scientific Applications:
- Chromatin accessibility profiling: Supports genome-wide studies of chromatin accessibility using ATAC-seq data.
- Regulatory element and transcription factor analysis: Enables identification and characterization of regulatory elements and transcription factor binding sites via peak calling, motif discovery, and footprinting.
- Epigenetics and variant analysis: Facilitates investigation of epigenetic modifications and SNP-associated differences in accessibility.
Methodology:
Computational steps explicitly include preprocessing of FASTQ files, read alignment (e.g., via Rbowtie2), operations on SAM/BAM/BED files, peak calling with F-seq, motif discovery, Gene Ontology (GO) analysis, SNP analysis, transcription factor footprinting, enrichment and advanced statistical analyses, and generation of quality control reports; implemented in R and C++ as an R/Bioconductor package.
Topics
Details
- License:
- GPL-3.0
- Tool Type:
- library
- Operating Systems:
- Linux, Windows, Mac
- Programming Languages:
- R, C++
- Added:
- 7/1/2018
- Last Updated:
- 11/25/2024
Operations
Publications
Wei Z, Zhang W, Fang H, Li Y, Wang X. esATAC: an easy-to-use systematic pipeline for ATAC-seq data analysis. Bioinformatics. 2018;34(15):2664-2665. doi:10.1093/bioinformatics/bty141. PMID:29522192. PMCID:PMC6061683.