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dCaP: detecting differential binding events in multiple conditions and proteins
BACKGROUND: Current ChIP-seq studies are interested in comparing multiple epigenetic profiles across several cell types and tissues simultaneously for studying constitutive and differential regulation. Simultaneous analysis of multiple epigenetic features in many samples can gain substantial power a...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4290593/ https://www.ncbi.nlm.nih.gov/pubmed/25522020 http://dx.doi.org/10.1186/1471-2164-15-S9-S12 |
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author | Chen, Kuan-Bei Hardison, Ross Zhang, Yu |
author_facet | Chen, Kuan-Bei Hardison, Ross Zhang, Yu |
author_sort | Chen, Kuan-Bei |
collection | PubMed |
description | BACKGROUND: Current ChIP-seq studies are interested in comparing multiple epigenetic profiles across several cell types and tissues simultaneously for studying constitutive and differential regulation. Simultaneous analysis of multiple epigenetic features in many samples can gain substantial power and specificity than analyzing individual features and/or samples separately. Yet there are currently few tools can perform joint inference of constitutive and differential regulation in multi-feature-multi-condition contexts with statistical testing. Existing tools either test regulatory variation for one factor in multiple samples at a time, or for multiple factors in one or two samples. Many of them only identify binary rather than quantitative variation, which are sensitive to threshold choices. RESULTS: We propose a novel and powerful method called dCaP for simultaneously detecting constitutive and differential regulation of multiple epigenetic factors in multiple samples. Using simulation, we demonstrate the superior power of dCaP compared to existing methods. We then apply dCaP to two datasets from human and mouse ENCODE projects to demonstrate its utility. We show in the human dataset that the cell-type specific regulatory loci detected by dCaP are significantly enriched near genes with cell-type specific functions and disease relevance. We further show in the mouse dataset that dCaP captures genomic regions showing significant signal variations for TAL1 occupancy between two mouse erythroid cell lines. The novel TAL1 occupancy loci detected only by dCaP are highly enriched with GATA1 occupancy and differential gene expression, while those detected only by other methods are not. CONCLUSIONS: Here, we developed a novel approach to utilize the cooperative property of proteins to detect differential binding given multivariate ChIP-seq samples to provide better power, aiming for complementing existing approaches and providing new insights in the method development in this field. |
format | Online Article Text |
id | pubmed-4290593 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-42905932015-01-15 dCaP: detecting differential binding events in multiple conditions and proteins Chen, Kuan-Bei Hardison, Ross Zhang, Yu BMC Genomics Research BACKGROUND: Current ChIP-seq studies are interested in comparing multiple epigenetic profiles across several cell types and tissues simultaneously for studying constitutive and differential regulation. Simultaneous analysis of multiple epigenetic features in many samples can gain substantial power and specificity than analyzing individual features and/or samples separately. Yet there are currently few tools can perform joint inference of constitutive and differential regulation in multi-feature-multi-condition contexts with statistical testing. Existing tools either test regulatory variation for one factor in multiple samples at a time, or for multiple factors in one or two samples. Many of them only identify binary rather than quantitative variation, which are sensitive to threshold choices. RESULTS: We propose a novel and powerful method called dCaP for simultaneously detecting constitutive and differential regulation of multiple epigenetic factors in multiple samples. Using simulation, we demonstrate the superior power of dCaP compared to existing methods. We then apply dCaP to two datasets from human and mouse ENCODE projects to demonstrate its utility. We show in the human dataset that the cell-type specific regulatory loci detected by dCaP are significantly enriched near genes with cell-type specific functions and disease relevance. We further show in the mouse dataset that dCaP captures genomic regions showing significant signal variations for TAL1 occupancy between two mouse erythroid cell lines. The novel TAL1 occupancy loci detected only by dCaP are highly enriched with GATA1 occupancy and differential gene expression, while those detected only by other methods are not. CONCLUSIONS: Here, we developed a novel approach to utilize the cooperative property of proteins to detect differential binding given multivariate ChIP-seq samples to provide better power, aiming for complementing existing approaches and providing new insights in the method development in this field. BioMed Central 2014-12-08 /pmc/articles/PMC4290593/ /pubmed/25522020 http://dx.doi.org/10.1186/1471-2164-15-S9-S12 Text en Copyright © 2014 Chen et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/4.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 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 | Research Chen, Kuan-Bei Hardison, Ross Zhang, Yu dCaP: detecting differential binding events in multiple conditions and proteins |
title | dCaP: detecting differential binding events in multiple conditions and proteins |
title_full | dCaP: detecting differential binding events in multiple conditions and proteins |
title_fullStr | dCaP: detecting differential binding events in multiple conditions and proteins |
title_full_unstemmed | dCaP: detecting differential binding events in multiple conditions and proteins |
title_short | dCaP: detecting differential binding events in multiple conditions and proteins |
title_sort | dcap: detecting differential binding events in multiple conditions and proteins |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4290593/ https://www.ncbi.nlm.nih.gov/pubmed/25522020 http://dx.doi.org/10.1186/1471-2164-15-S9-S12 |
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