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De novo ChIP-seq analysis

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...

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Autores principales: He, Xin, Cicek, A. Ercument, Wang, Yuhao, Schulz, Marcel H., Le, Hai-Son, Bar-Joseph, Ziv
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4579611/
https://www.ncbi.nlm.nih.gov/pubmed/26400819
http://dx.doi.org/10.1186/s13059-015-0756-4
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author He, Xin
Cicek, A. Ercument
Wang, Yuhao
Schulz, Marcel H.
Le, Hai-Son
Bar-Joseph, Ziv
author_facet He, Xin
Cicek, A. Ercument
Wang, Yuhao
Schulz, Marcel H.
Le, Hai-Son
Bar-Joseph, Ziv
author_sort He, Xin
collection PubMed
description 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13059-015-0756-4) contains supplementary material, which is available to authorized users.
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spelling pubmed-45796112015-09-24 De novo ChIP-seq analysis He, Xin Cicek, A. Ercument Wang, Yuhao Schulz, Marcel H. Le, Hai-Son Bar-Joseph, Ziv Genome Biol Method 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13059-015-0756-4) contains supplementary material, which is available to authorized users. BioMed Central 2015-09-23 2015 /pmc/articles/PMC4579611/ /pubmed/26400819 http://dx.doi.org/10.1186/s13059-015-0756-4 Text en © He et al. 2015 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Method
He, Xin
Cicek, A. Ercument
Wang, Yuhao
Schulz, Marcel H.
Le, Hai-Son
Bar-Joseph, Ziv
De novo ChIP-seq analysis
title De novo ChIP-seq analysis
title_full De novo ChIP-seq analysis
title_fullStr De novo ChIP-seq analysis
title_full_unstemmed De novo ChIP-seq analysis
title_short De novo ChIP-seq analysis
title_sort de novo chip-seq analysis
topic Method
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4579611/
https://www.ncbi.nlm.nih.gov/pubmed/26400819
http://dx.doi.org/10.1186/s13059-015-0756-4
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