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Discovering transcriptional modules by Bayesian data integration
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Savage, Richard S., Ghahramani, Zoubin, Griffin, Jim E., De la Cruz, Bernard J. and Wild, David L. (2010) Discovering transcriptional modules by Bayesian data integration. Bioinformatics, Vol.26 (No.12). pp. 158-167. doi:10.1093/bioinformatics/btq210 ISSN 1367-4803.
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Official URL: http://dx.doi.org/10.1093/bioinformatics/btq210
Abstract
Motivation: We present a method for directly inferring transcriptional modules (TMs) by integrating gene expression and transcription factor binding (ChIP-chip) data. Our model extends a hierarchical Dirichlet process mixture model to allow data fusion on a gene-by-gene basis. This encodes the intuition that co-expression and co-regulation are not necessarily equivalent and hence we do not expect all genes to group similarly in both datasets. In particular, it allows us to identify the subset of genes that share the same structure of transcriptional modules in both datasets.
Results: We find that by working on a gene-by-gene basis, our model is able to extract clusters with greater functional coherence than existing methods. By combining gene expression and transcription factor binding (ChIP-chip) data in this way, we are better able to determine the groups of genes that are most likely to represent underlying TMs.
Item Type: | Journal Article | ||||
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Subjects: | Q Science > QA Mathematics Q Science > QH Natural history |
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Divisions: | Faculty of Science, Engineering and Medicine > Research Centres > Warwick Systems Biology Centre | ||||
Library of Congress Subject Headings (LCSH): | Genes -- Research, Gene expression, Transcription factors, Dirichlet principle | ||||
Journal or Publication Title: | Bioinformatics | ||||
Publisher: | Oxford University Press | ||||
ISSN: | 1367-4803 | ||||
Official Date: | 15 June 2010 | ||||
Dates: |
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Volume: | Vol.26 | ||||
Number: | No.12 | ||||
Page Range: | pp. 158-167 | ||||
DOI: | 10.1093/bioinformatics/btq210 | ||||
Status: | Peer Reviewed | ||||
Access rights to Published version: | Open Access (Creative Commons) | ||||
Funder: | Engineering and Physical Sciences Research Council (EPSRC) | ||||
Grant number: | EP/F027400/1 (EPSRC) |
Data sourced from Thomson Reuters' Web of Knowledge
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