deeptools

Automate ChIP-seq analysis by providing BAM alignment files and BED peaks to generate heatmaps and enrichment plots. This streamlines the workflow from raw alignments to visualization without manual scripting.

Normalize NGS data for sample comparison using RPGC, CPM, RPKM, BPM, or none methods. This ensures accurate quantitative comparisons across replicate sequences and different experimental conditions.

Perform quality control on ATAC-seq and RNA-seq experiments through fingerprint, PCA, and coverage assessments. This validates data integrity and identifies outliers before proceeding with downstream analysis.

deepTools requires pybigwig and numpy dependencies to efficiently handle genomic data processing. These packages enable the computational backend for reading large alignment files and calculating coverage metrics.

Visualize high-throughput sequencing data using heatmaps, profiles, and enrichment plots. These visualizations support ChIP-seq, RNA-seq, and ATAC-seq experiments to reveal genomic binding and expression patterns.

Generate a ChIP-seq analysis script by running the workflow generator with input BAM files, BED peaks, and genome size parameters. This creates an executable shell script automating the entire pipeline.