GliomaPredict: a clinically useful tool for assigning glioma patients to specific molecular subtypes.

ABSTRACT:

Background

Advances in generating genome-wide gene expression data have accelerated the development of molecular-based tumor classification systems. Tools that allow the translation of such molecular classification schemas from research into clinical applications are still missing in the emerging era of personalized medicine.

Results

We developed GliomaPredict as a computational tool that allows the fast and reliable classification of glioma patients into one of six previously published stratified subtypes based on sets of extensively validated classifiers derived from hundreds of glioma transcriptomic profiles. Our tool utilizes a principle component analysis (PCA)-based approach to generate a visual representation of the analyses, quantifies the confidence of the underlyin

SUBMITTER: Li A 

PROVIDER: S-EPMC2912783 | biostudies-literature | 2010 Jul

REPOSITORIES: biostudies-literature