Research Repository

Joint modeling of ChIP-seq data via a Markov random field model

Bao, Yanchun and Vinciotti, Veronica and Wit, Ernst and 't Hoen, Peter AC (2014) 'Joint modeling of ChIP-seq data via a Markov random field model.' Biostatistics, 15 (2). pp. 296-310. ISSN 1465-4644

Full text not available from this repository.


Chromatin ImmunoPrecipitation-sequencing (ChIP-seq) experiments have now become routine in biology for the detection of protein-binding sites. In this paper, we present a Markov random field model for the joint analysis of multiple ChIP-seq experiments. The proposed model naturally accounts for spatial dependencies in the data, by assuming first-order Markov dependence and, for the large proportion of zero counts, by using zero-inflated mixture distributions. In contrast to all other available implementations, the model allows for the joint modeling of multiple experiments, by incorporating key aspects of the experimental design. In particular, the model uses the information about replicates and about the different antibodies used in the experiments. An extensive simulation study shows a lower false non-discovery rate for the proposed method, compared with existing methods, at the same false discovery rate. Finally, we present an analysis on real data for the detection of histone modifications of two chromatin modifiers from eight ChIP-seq experiments, including technical replicates with different IP efficiencies.

Item Type: Article
Uncontrolled Keywords: Models, Statistical; Markov Chains; Statistical Distributions; Chromatin Immunoprecipitation; Sequence Analysis, DNA; Protein Binding
Subjects: Q Science > QA Mathematics
Q Science > QH Natural history > QH301 Biology
Divisions: Faculty of Science and Health
Faculty of Science and Health > Mathematical Sciences, Department of
SWORD Depositor: Elements
Depositing User: Elements
Date Deposited: 04 Dec 2015 13:13
Last Modified: 15 Jan 2022 00:55

Actions (login required)

View Item View Item