M3C: Monte Carlo reference-based consensus clustering
Abstract
Genome-wide data is used to stratify patients into classes for precision medicine using clustering algorithms. A common problem in this area is selection of the number of clusters (K). The Monti consensus clustering algorithm is a widely used method which uses stability selection to estimate K. However, the method has bias towards higher values of K and yields high numbers of false positives. As a solution, we developed Monte Carlo...
Paper Details
Title
M3C: Monte Carlo reference-based consensus clustering
Published Date
Feb 4, 2020
Journal
Volume
10
Issue
1
Pages
1816 - 1816
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