With the advent of ultra-high-throughput sequencing technologies, ChIP-seq is
becoming the main stream for the genome-wide studies of transcription factor binding sites
(TFBSs) and histone modification sites. Computational analysis of ChIP-seq data is
important for ChIP-seq applications. In this chapter, we first give an overview of the stateof-
the-art ChIP-seq analysis tools developed for predicting ChIP-enriched genomic sites.
Next, we describe the methods employed in a comprehensive analysis on Chen et al.’s
ChIP-seq dataset in mouse embryonic stem cells (mESC) [1]. These methods include the
prediction of transcription factor binding peaks, as well as subsequent analysis procedures
such as de novo motif-finding and the discovery of transcription factor co-localization. By
this, we demonstrate how the computational approaches assist to achieve novel biological
discoveries from large-scale ChIP-seq dataset.
Keywords: Computational Analysis, Sequencing, Transcriptional regulation,
Chromatin Immuno-precipitation, Histone modification, ChIP-seq, ChIP-enriched
loci, Hidden Markov Model, Control library, Poisson distribution, mESC.
