DIABLO: an integrative approach for identifying key molecular drivers from multi-omics assays.

ABSTRACT:

Motivation

In the continuously expanding omics era, novel computational and statistical strategies are needed for data integration and identification of biomarkers and molecular signatures. We present Data Integration Analysis for Biomarker discovery using Latent cOmponents (DIABLO), a multi-omics integrative method that seeks for common information across different data types through the selection of a subset of molecular features, while discriminating between multiple phenotypic groups.

Results

Using simulations and benchmark multi-omics studies, we show that DIABLO identifies features with superior biological relevance compared with existing unsupervised integrative methods, while achieving predictive performance comparable to state-of-the-art supervised approaches. DIABL

SUBMITTER: Singh A 

PROVIDER: S-EPMC6735831 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature