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.

PMID: 29522192
PMCID: PMC6061683
Funding: - National Science Foundation of China: 31371341, 61721003, 61773230 - Tsinghua University Initiative Scientific Research Program: 20141081175

Documentation