Strategy to find molecular signatures in a small series of rare cancers: validation for radiation-induced breast and thyroid tumors.

ABSTRACT: Methods of classification using transcriptome analysis for case-by-case tumor diagnosis could be limited by tumor heterogeneity and masked information in the gene expression profiles, especially as the number of tumors is small. We propose a new strategy, EMts_2PCA, based on: 1) The identification of a gene expression signature with a great potential for discriminating subgroups of tumors (EMts stage), which includes: a) a learning step, based on an expectation-maximization (EM) algorithm, to select sets of candidate genes whose expressions discriminate two subgroups, b) a training step to select from the sets of candidate genes those with the highest potential to classify training tumors, c) the compilation of genes selected during the training step, and standardization of their levels of

SUBMITTER: Ugolin N 

PROVIDER: S-EPMC3154936 | biostudies-literature | 2011

REPOSITORIES: biostudies-literature