Bioinformatics Advance Access published online on October 30, 2008
Bioinformatics, doi:10.1093/bioinformatics/btn553
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Investigating the correspondence between transcriptomic and proteomic expression profiles using coupled cluster models.
1Department of Computing Science, University of Glasgow, Glasgow, G12 8QQ, UK
2Beatson Institute for Cancer Research, Signalling and Proteomics Laboratory, Garscube Estate, Glasgow, G61 1BD,UK
3Institute of Biomedical and Life Sciences, Sir Henry Wellcome Functional Genomics Facillity, University of Glasgow, G12 8QQ, UK 4Systems Biology Program, Pacific Northwest National Laboratory, Richland, WA 99352, USA
5Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA 99352, USA
*To whom correspondence should be addressed. Dr. Simon Rogers, E-mail: srogers{at}dcs.gla.ac.uk
 |
Abstract |
|---|
Motivation: Modern transcriptomics and proteomics enable us to survey the expression of RNAs and proteins at large scales. While these data are usually generated and analysed separately, there is an increasing interest in comparing and co-analysing transcriptome and proteome expression data. A major open question is whether transcriptome and proteome expression is linked and how it is coordinated.
Results: Here we have developed a probabilistic clustering model that permits analysis of the links between transcriptomic and proteomic profiles in a sensible and flexible manner. Our coupled mixture model defines a prior probability distribution over the component to which a protein profile should be assigned conditioned on which component the associated mRNA profile belongs to. We apply this approach to a large dataset of quantitative transcriptomic and proteomic expression data obtained from a human breast epithelial cell line (HMEC). The results reveal a complex relationship between transcriptome and proteome with most mRNA clusters linked to at least two protein clusters, and vice versa. A more detailed analysis incorporating information on gene function from the gene ontology database shows that a high correlation of mRNA and protein expression is limited to the components of some molecular machines, such as the ribosome, cell adhesion complexes and the TCP-1 chaperonin involved in protein folding.
Availability: Matlab code is available from the authors on request.
Contact: mailto:srogers{at}dcs.gla.ac.uk
Associate Editor: Prof. Ivo Hofacker
Received on August 27, 2008; revised on October 13, 2008; accepted on October 22, 2008
CiteULike 
Connotea 
Del.icio.us What's this?
This article has been cited by other articles:
|
|
 |
|
  M. F. Ochs Knowledge-based data analysis comes of age Brief Bioinform, October 23, 2009; (2009) bbp044v1. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 S. Dong, K. L. Replogle, L. Hasadsri, B. S. Imai, P. M. Yau, S. Rodriguez-Zas, B. R. Southey, J. V. Sweedler, and D. F. Clayton Discrete molecular states in the brain accompany changing responses to a vocal signal PNAS, July 7, 2009; 106(27): 11364 - 11369. [Abstract] [Full Text] [PDF]
|
|