Zero-Inflated Models to Identify Transcription Factor Binding Sites in ChIP-seq Experiments

<p>It is essential to determine the protein-DNA binding sites to understand many biological processes. A transcription factor is a particular type of protein that binds to DNA and controls gene regulation in living organisms. Chromatin immunoprecipitation followed by highthroughput sequencing (ChIP-seq) is considered the gold standard in locating these binding sites and programs use to identify DNA-transcription factor binding sites are known as peak-callers. ChIP-seq data are known to exhibit considerable background noise and other biases. In this study, we propose a negative binomial model (NB), a zero-inflated Poisson model (ZIP) and a zero-inflated negative binomial model (ZINB) for peak-calling. Using real ChIP-seq datasets, we show that ZINB model is the best model for ChIP-seq data. Then we incorporate control data, GC count information, and mappability information into the ZINB regression model as covariates using two link functions. We implemented this approach in C++, and our peak-caller chooses the optimal parameter combination for a given dataset. Performace of our approach is compared with two frequently used peak-callers: QuEST and MACS.</p>

Name thesis:degree_name

Doctor of Philosophy (PhD)

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Mathematics & Statistics

Year dc:date.available

2015

Author dc:creator

• Viswakula, Sameera Dhananjaya

Contributors dc:contributor

• Norou Diawara
• Nak-Kyeong Kim
• N. Rao Chaganty
• Michael Doviak

• ChIP-seq data
• Count data
• DNA-protein binding sites
• Next generation sequencing
• Applied Statistics
• Bioinformatics
• Biostatistics

Statement dc:rights

• <p>In Copyright. URI: <a href="http://rightsstatements.org/vocab/InC/1.0/">http://rightsstatements.org/vocab/InC/1.0/</a> This Item is protected by copyright and/or related rights. You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s).</p>

Identifier

9781321843439

OAI identifier oai:identifier

oai:digitalcommons.odu.edu:mathstat_etds-1068