ChIP-Seq has become the standard method for genome-wide profiling DNA association
of transcription factors. To simplify analyzing and interpreting ChIP-Seq data,
which typically involves using multiple applications, we describe an integrated,
open source, R-based analysis pipeline. The pipeline addresses data input, peak
detection, sequence and motif analysis, visualization, and data export, and can
readily be extended via other R and Bioconductor packages. Using a standard
multicore computer, it can be used with datasets consisting of tens of thousands
of enriched regions. We demonstrate its effectiveness on published human
ChIP-Seq datasets for FOXA1, ER, CTCF and STAT1, where it detected co-occurring
motifs that were consistent with the literature but not detected by other
methods. Our pipeline provides the first complete set of Bioconductor tools for
sequence and motif analysis of ChIP-Seq and ChIP-chip data.