01778nas a2200229   4500008004100000245010300041210006900144300001100213490000700224520087500231653007101106653013601177100001501313700001201328700002201340700001801362700001301380700001701393700001701410700001501427856010601442       2008                        eng d00aDirect functional assessment of the composite phenotype through multivariate projection strategies0 aDirect functional assessment of the composite phenotype through   a373-830 v923 a<p>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.</p>10aBreast Neoplasms/genetics Computational Biology/*methods Databases10aGenetic Female Gene Expression Profiling/*statistics & numerical data Humans Mathematical Computing Multivariate Analysis Phenotype1 aConesa, A.1 aBro, R.1 aGarcia-Garcia, F.1 aPrats, J., M.1 aGotz, S.1 aKjeldahl, K.1 aMontaner, D.1 aDopazo, J.  uhttp://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=18652888