Cross cell type inference of TF binding by integrative analysis of TF ChIP-seq and chromatin accessibility profiles

Transcription factors (TF) are proteins that drive and maintain cellular functions by physically binding to DNA and regulating the expression levels of other genes. There are approximately 1,600 TFs in the human genome. Accurate and scalable identification of TF binding locations across the entire genome remains a major challenge. An effective solution to this problem would have overarching implications for understanding disease mechanisms and development of therapeutics. In this project, we devise a simple and elegant solution to this problem by jointly analyzing complementary data types. We will perform a formal evaluation of this novel approach by using publicly available data sets. Additionally, we will develop a reusable analysis pipeline to deploy this technology in order to enable efficient annotation of genome wide TF binding sites with cell type specificity.

Faculty Supervisor:

Paul Pavlidis

Student:

Ching-Pan (Eric) Chu

Partner:

Koonkie Canada Inc

Discipline:

Other

Sector:

Professional, scientific and technical services

University:

University of British Columbia