Comparison and evaluation of pathway-level aggregation methods of gene expression data.

ABSTRACT:

Background

Microarray experiments produce expression measurements in genomic scale. A way to derive functional understanding of the data is to focus on functional sets of genes, such as pathways, instead of individual genes. While a common practice for the pathway-level analysis has been functional enrichment analysis such as over-representation analysis and gene set enrichment analysis, an alternative approach has also been explored. In this approach, gene expression data are first aggregated at pathway level to transform the original data into a compact representation in which each row corresponds to a pathway instead of a gene. Thereafter the pathway expression data can be used for differential expression and classification analyses in pathway space, leveraging existing algorith

SUBMITTER: Hwang S 

PROVIDER: S-EPMC3521227 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature