ChIP-Seq is extensively used to characterize genome-wide binding patterns of transcription factors and other chromatin-associated proteins.
Mapping the chromosomal locations where specific DNA-binding enzymes, modified histones, chaperones, nucleosomes, and transcription factors bind can elucidate the role of these protein-DNA interactions in gene expression and other cellular processes.
However, sole mapping is not enough. Comparative ChIP-seq analysis, i.e. identification of sites that are differentially bound between two sample groups (conditions or tissues), provides different snapshots of a binding signals uncovering specific patterns of gene regulation.
We implemented quantitative comparison of ChIP-Seq data sets that includes overlapping and merging peak sets, counting sequencing reads overlapping intervals in peak sets, and identifying statistically significantly differentially bound sites based on evidence of binding affinity (measured by differences in read densities).
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