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Exon level integration of proteomics and microarray data

Bitton, DA; Okoniewski, MJ; Connolly, Y; Miller, CJ; (2008) Exon level integration of proteomics and microarray data. BMC BIOINFORMATICS , 9 , Article 118. 10.1186/1471-2105-9-118. Green open access

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Abstract

Background: Previous studies comparing quantitative proteomics and microarray data have generally found poor correspondence between the two. We hypothesised that this might in part be because the different assays were targeting different parts of the expressed genome and might therefore be subjected to confounding effects from processes such as alternative splicing.Results: Using a genome database as a platform for integration, we combined quantitative protein mass spectrometry with Affymetrix Exon array data at the level of individual exons. We found significantly higher degrees of correlation than have been previously observed (r = 0.808). The study was performed using cell lines in equilibrium in order to reduce a major potential source of biological variation, thus allowing the analysis to focus on the data integration methods in order to establish their performance.Conclusion: We conclude that part of the variation observed when integrating microarray and proteomics data may occur as a consequence both of the data analysis and of the high granularity to which studies have until recently been limited. The approach opens up the possibility for the first time of considering combined microarray and proteomics datasets at the level of individual exons and isoforms, important given the high proportion of alternative splicing observed in the human genome.

Type: Article
Title: Exon level integration of proteomics and microarray data
Open access status: An open access version is available from UCL Discovery
DOI: 10.1186/1471-2105-9-118
Publisher version: http://dx.doi.org/10.1186/1471-2105-9-118
Language: English
Additional information: © 2008 Bitton 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.
Keywords: GENE-EXPRESSION, PROTEIN, CELLS, ANNOTATION, PROBESETS, SUMMARIES, COMPLEX, TAGS, CALL
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences
URI: https://discovery.ucl.ac.uk/id/eprint/1325269
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