|Title||Direct functional assessment of the composite phenotype through multivariate projection strategies|
|Publication Type||Journal Article|
|Year of Publication||2008|
|Authors||Conesa, A, Bro, R, Garcia-Garcia, F, Prats, JM, Gotz, S, Kjeldahl, K, Montaner, D, Dopazo, J|
|Keywords||Breast Neoplasms/genetics Computational Biology/*methods Databases; Genetic Female Gene Expression Profiling/*statistics & numerical data Humans Mathematical Computing Multivariate Analysis Phenotype|
We present a novel approach for the analysis of transcriptomics data that integrates functional annotation of gene sets with expression values in a multivariate fashion, and directly assesses the relation of functional features to a multivariate space of response phenotypical variables. Multivariate projection methods are used to obtain new correlated variables for a set of genes that share a given function. These new functional variables are then related to the response variables of interest. The analysis of the principal directions of the multivariate regression allows for the identification of gene function features correlated with the phenotype. Two different transcriptomics studies are used to illustrate the statistical and interpretative aspects of the methodology. We demonstrate the superiority of the proposed method over equivalent approaches.
Conesa, Ana Bro, Rasmus Garcia-Garcia, Francisco Prats, Jose Manuel Gotz, Stefan Kjeldahl, Karin Montaner, David Dopazo, Joaquin Evaluation Studies Research Support, Non-U.S. Gov’t United States Genomics Genomics. 2008 Dec;92(6):373-83. Epub 2008 Sep 13.