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DC Field | Value | Language |
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dc.contributor.author | Bao, Y | - |
dc.contributor.author | Vinciotti, V | - |
dc.contributor.author | Wit, E | - |
dc.contributor.author | 't Hoen, PAC | - |
dc.date.accessioned | 2014-02-03T14:48:27Z | - |
dc.date.available | 2014-02-03T14:48:27Z | - |
dc.date.issued | 2013 | - |
dc.identifier.citation | BMC Bioinformatics, 14, Article number, 169, 2013 | en_US |
dc.identifier.issn | 1471-2105 | - |
dc.identifier.uri | http://www.biomedcentral.com/1471-2105/14/169 | en |
dc.identifier.uri | http://bura.brunel.ac.uk/handle/2438/7981 | - |
dc.description | This article is made available through the Brunel Open Access Publishing Fund. © 2013 Bao et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. | en_US |
dc.description.abstract | Background: ImmunoPrecipitation (IP) efficiencies may vary largely between different antibodies and between repeated experiments with the same antibody. These differences have a large impact on the quality of ChIP-seq data: a more efficient experiment will necessarily lead to a higher signal to background ratio, and therefore to an apparent larger number of enriched regions, compared to a less efficient experiment. In this paper, we show how IP efficiencies can be explicitly accounted for in the joint statistical modelling of ChIP-seq data. Results: We fit a latent mixture model to eight xperiments on two proteins, from two laboratories where different antibodies are used for the two proteins. We use the model parameters to estimate the efficiencies of individual experiments, and find that these are clearly different for the different laboratories, and amongst technical replicates from the same lab. When we account for ChIP efficiency, we find more regions bound in the more efficient experiments than in the less efficient ones, at the same false discovery rate. A priori knowledge of the same umber of binding sites across experiments can also be included in the model for a more robust detection of differentially bound regions among two different proteins. Conclusions: We propose a statistical model for the detection of enriched and differentially bound regions from multiple ChIP-seq data sets. The framework that we present accounts explicitly for IP efficiencies in ChIP-seq data, and allows to model jointly, rather than individually, replicates and experiments from different proteins, leading to more robust biological conclusions. | en_US |
dc.description.sponsorship | Biotechnology and Biological Sciences Research Council, the European Commission 7th Framework Program GEUVADIS and the Centre for Medical Systems Biology within the framework of the Netherlands Genomics Initiative/Netherlands Organisation for Scientific Research. | en_US |
dc.language | English | - |
dc.language.iso | en | en_US |
dc.publisher | BioMed Central LTD | en_US |
dc.subject | ImmunoPrecipitation | en_US |
dc.subject | ChIP-seq data | en_US |
dc.subject | Antibodies | en_US |
dc.subject | Joint statistical modelling | en_US |
dc.title | Accounting for immunoprecipitation efficiencies in the statistical analysis of ChIP-seq data | en_US |
dc.type | Article | en_US |
dc.identifier.doi | http://dx.doi.org/10.1186/1471-2105-14-169 | - |
pubs.organisational-data | /Brunel | - |
pubs.organisational-data | /Brunel/Brunel Active Staff | - |
pubs.organisational-data | /Brunel/Brunel Active Staff/School of Info. Systems, Comp & Maths | - |
pubs.organisational-data | /Brunel/Brunel Active Staff/School of Info. Systems, Comp & Maths/Maths | - |
pubs.organisational-data | /Brunel/University Research Centres and Groups | - |
pubs.organisational-data | /Brunel/University Research Centres and Groups/School of Health Sciences and Social Care - URCs and Groups | - |
pubs.organisational-data | /Brunel/University Research Centres and Groups/School of Health Sciences and Social Care - URCs and Groups/Centre for Systems and Synthetic Biology | - |
pubs.organisational-data | /Brunel/University Research Centres and Groups/School of Information Systems, Computing and Mathematics - URCs and Groups | - |
pubs.organisational-data | /Brunel/University Research Centres and Groups/School of Information Systems, Computing and Mathematics - URCs and Groups/Centre for the Analysis of Risk and Optimisation Modelling Applications | - |
Appears in Collections: | Publications Computer Science Brunel OA Publishing Fund Dept of Mathematics Research Papers |
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