CC-PROMISE effectively integrates two forms of molecular data with multiple biologically related endpoints.

ABSTRACT:

Background

As new technologies allow investigators to collect multiple forms of molecular data (genomic, epigenomic, transcriptomic, etc) and multiple endpoints on a clinical trial cohort, it will become necessary to effectively integrate all these data in a way that reliably identifies biologically important genes.

Methods

We introduce CC-PROMISE as an integrated data analysis method that combines components of canonical correlation (CC) and projection onto the most interesting evidence (PROMISE). For each gene, CC-PROMISE first uses CC to compute scores that represent the association of two forms of molecular data with each other. Next, these scores are substituted into PROMISE to evaluate the statistical evidence that the molecular data show a biologically meaningful rela

SUBMITTER: Cao X 

PROVIDER: S-EPMC5073973 | biostudies-literature | 2016 Oct

REPOSITORIES: biostudies-literature