Identification of candidate cancer drivers by integrative Epi-DNA and Gene Expression (iEDGE) data analysis
Abstract
The emergence of large-scale multi-omics data warrants method development for data integration. Genomic studies from cancer patients have identified epigenetic and genetic regulators – such as methylation marks, somatic mutations, and somatic copy number alterations (SCNAs), among others – as predictive features of cancer outcome. However, identification of “driver genes” associated with a given alteration remains a challenge. To this end, we...
Paper Details
Title
Identification of candidate cancer drivers by integrative Epi-DNA and Gene Expression (iEDGE) data analysis
Published Date
Nov 15, 2019
Journal
Volume
9
Issue
1
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