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

@article{citeulike:5649643, 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. Availability: 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. Contact: k.lecao@uq.edu.au Supplementary information: Supplementary data are available at Bioinformatics online. 10.1093/bioinformatics/btp515}, author = {Le Cao, Kim-Anh and Gonzalez, Ignacio and Dejean, Sebastien}, citeulike-article-id = {5649643}, citeulike-linkout-0 = {http://dx.doi.org/10.1093/bioinformatics/btp515}, citeulike-linkout-1 = {http://bioinformatics.oxfordjournals.org/content/25/21/2855.abstract}, citeulike-linkout-2 = {http://bioinformatics.oxfordjournals.org/content/25/21/2855.full.pdf}, citeulike-linkout-3 = {http://view.ncbi.nlm.nih.gov/pubmed/19706745}, citeulike-linkout-4 = {http://www.hubmed.org/display.cgi?uids=19706745}, day = {1}, doi = {10.1093/bioinformatics/btp515}, issn = {1460-2059}, journal = {Bioinformatics}, keywords = {bioconductor, correlation, datasets, integration, integromics, omics, r, relationships}, month = {November}, number = {21}, pages = {2855--2856}, posted-at = {2009-11-06 17:20:25}, priority = {2}, title = {integrOmics: an R package to unravel relationships between two omics datasets}, url = {http://dx.doi.org/10.1093/bioinformatics/btp515}, volume = {25}, year = {2009} }

TY - JOUR ID - citeulike:5649643 L3 - citeulike-article-id:5649643 N2 - 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. Availability: 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. Contact: k.lecao@uq.edu.au Supplementary information: Supplementary data are available at Bioinformatics online. 10.1093/bioinformatics/btp515 IS - 21 JF - Bioinformatics SN - 1460-2059 EP - 2856 TI - integrOmics: an R package to unravel relationships between two omics datasets VL - 25 SP - 2855 KW - bioconductor KW - correlation KW - datasets KW - integration KW - integromics KW - omics KW - r KW - relationships AU - Le Cao, Kim-Anh AU - Gonzalez, Ignacio AU - Dejean, Sebastien PY - 2009/11/01/ UR - http://dx.doi.org/10.1093/bioinformatics/btp515 ER -