Computational algorithm development for epigenomic analysis

Multiple computational algorithms were developed for analyzing ChIP-seq datasets of histone modifications. For basic ChIP-seq data processing, the problems of ambiguous short sequence read mapping and broad peak calling of diffuse ChIP-seq signals were solved by novel statistical methods. Their performance was systematically evaluated compared with existing approaches. The potential utility of finding meaningful biological information was demonstrated by the applications on real datasets. For biological question driven data mining, several important topics were selected for algorithm developments, including hypothesis-driven insulator prediction, unbiased chromatin boundary element discovery and combinatorial histone modification signature inference. The integrative computational pipeline for insulator prediction not only produced a list of putative insulators but also recovered specific associated chromatin and functional features. Selected predictions have been experimentally validated. The unbiased chromatin boundary element prediction algorithm was feature-free and had the capability to discover novel types of boundary elements. The predictions found a set of chromatin features and provided the first report of tRNA-derived boundary elements in the human genome. The combinatorial chromatin signature algorithm employed chromatin profile alignments for unsupervised inferences of histone modification patterns. The signatures were associated with various regulatory elements and functional activities. Both the computational advantages and the biological discoveries were discussed.

Department dc:contributor.department

Biology

Grantor dc:publisher

Georgia Institute of Technology

Year dc:date.issued

2012

Author dc:creator

• Wang, Jianrong

Advisor dc:contributor.advisor

• Jordan, I. King

Committee members dc:contributor.committeemember

• Borodovsky, Mark
• Fan, Yuhong
• McDonald, John
• Yi, Soojin

• ChIP-seq
• Histone modifications
• Bioinformatics
• Epigenetics
• Insulators

Language dc:language.iso

en_US

Handle dc:identifier.uri

http://hdl.handle.net/1853/48984

OAI identifier oai:identifier

oai:repository.gatech.edu:1853/48984