integrOmics: an R package to unravel relationships between two omics datasets

Le Cao, Kim-Anh, Gonzalez, Ignacio and Dejean, Sébastien (2009) integrOmics: an R package to unravel relationships between two omics datasets. Bioinformatics, 25 21: 2855-2856. doi:10.1093/bioinformatics/btp515

Author Le Cao, Kim-Anh
Gonzalez, Ignacio
Dejean, Sébastien
Title integrOmics: an R package to unravel relationships between two omics datasets
Journal name Bioinformatics   Check publisher's open access policy
ISSN 1367-4803
Publication date 2009-11
Year available 2009
Sub-type Article (original research)
DOI 10.1093/bioinformatics/btp515
Volume 25
Issue 21
Start page 2855
End page 2856
Total pages 2
Editor David Prosser
Place of publication Oxford, U.K
Publisher Oxford University Press
Collection year 2010
Language eng
Subject C1
970106 Expanding Knowledge in the Biological Sciences
060102 Bioinformatics
Abstract Motivation: With the availability of many ‘omics’ data, such as transcriptomics, proteomics or metabolomics, the integrative or joint analysis of multiple datasets from different technology platforms is becoming crucial to unravel the relationships between different biological functional levels. However, the development of such an analysis is a major computational and technical challenge as most approaches suffer from high data dimensionality. New methodologies need to be developed and validated. Results: integrOmics efficiently performs integrative analyses of two types of ‘omics’ variables that are measured on the same samples. It includes a regularized version of canonical correlation analysis to enlighten correlations between two datasets, and a sparse version of partial least squares (PLS) regression that includes simultaneous variable selection in both datasets. The usefulness of both approaches has been demonstrated previously and successfully applied in various integrative studies.
Q-Index Code C1
Q-Index Status Confirmed Code
Additional Notes First published online August 25, 2009.

Document type: Journal Article
Sub-type: Article (original research)
Collections: 2010 Higher Education Research Data Collection
Institute for Molecular Bioscience - Publications
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Citation counts: TR Web of Science Citation Count  Cited 102 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 115 times in Scopus Article | Citations
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Created: Thu, 12 Nov 2009, 11:54:47 EST by Mr Andrew Martlew on behalf of Institute for Molecular Bioscience