title: integrOmics: an R package to unravel relationships between two omics datasets.
abstract: BACKGROUND
  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.
  
  
  BACKGROUND
  integrOmics is freely available from http://CRAN.R-project.org/ or from the web site companion (http://math.univ-toulouse.fr/biostat) that provides full documentation and tutorials.
  
  
  BACKGROUND
  k.lecao@uq.edu.au
  
  
  BACKGROUND
  Supplementary data are available at Bioinformatics online.
authors.affiliation: Institute for Molecular Biosciences and ARC Centre of Excellence in Bioinformatics,The University of Queensland, Brisbane QLD 4072, Australia. k.lecao@uq.edu.au
authors.forename: Kim-Anh
authors.initials: KA
authors.lastname: Lê Cao
authors.forename: Ignacio
authors.initials: I
authors.lastname: González
authors.forename: Sébastien
authors.initials: S
authors.lastname: Déjean
mesh_terms: D019295:Computational Biology / Q000379:methods*; D016208:Databases, Factual; D023281:Genomics; D055432:Metabolomics; D040901:Proteomics; D012984:Software
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