TF-differential-binding

Differential binding analysis identifies differentially bound transcription factor regions from ChIP-seq data by using DiffBind in R to count reads, normalize, and statistically test for significant occupancy changes between conditions.

DiffBind compares wild-type vs mutant TF occupancy by applying contrasts across multiple conditions or cell types, counting reads within consensus peaksets, and performing statistical testing to reveal condition-specific regulatory changes.

ChIP-seq differential binding analysis requires a proper sample sheet with BAM and peak files organized by condition, along with a consistent genome build, to generate a DBA object for counting and statistical testing.

DiffBind supports multi-condition comparisons including treatment vs control analyses by generating contrasts from a DBA object, performing read counting, normalization, and statistical testing to identify differentially bound regions.

DiffBind differential binding analysis produces PCA plots, heatmaps, and volcano plots to visualize sample clustering and differential peak distributions, alongside exporting differential peak sets for downstream genomic analysis.