Compound Analytics using Combinatorics for Feature Selection: A Case Study in Biomarker Detection

Abstract

Computer and data scientists are increasingly tasked with analyzing data growing at unprecedented rates. These data frequently involve a high level of dimensionality. In this work, we present a novel method for dimension reduction that combines statistical scoring with graph theoretical filtering to distill salient features for machine learning. We apply this method to the timely problem of detecting epigenetic biomarkers in DNA methylation data.