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De novo ChIP-seq analysis

Author(s)
He, Xin; Cicek, A. Ercument; Wang, Yuhao; Schulz, Marcel H.; Le, Hai-Son; Bar-Joseph, Ziv; ... Show more Show less
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Abstract
Methods for the analysis of chromatin immunoprecipitation sequencing (ChIP-seq) data start by aligning the short reads to a reference genome. While often successful, they are not appropriate for cases where a reference genome is not available. Here we develop methods for de novo analysis of ChIP-seq data. Our methods combine de novo assembly with statistical tests enabling motif discovery without the use of a reference genome. We validate the performance of our method using human and mouse data. Analysis of fly data indicates that our method outperforms alignment based methods that utilize closely related species.
Date issued
2015-09
URI
http://hdl.handle.net/1721.1/98902
Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory; Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Journal
Genome Biology
Publisher
BioMed Central
Citation
He, Xin, A. Ercument Cicek, Yuhao Wang, Marcel H. Schulz, Hai-Son Le, and Ziv Bar-Joseph. "De novo ChIP-seq analysis." Genome Biology. 2015 Sep 23;16(1):205.
Version: Final published version
ISSN
1474-760X

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