CLIMB: High-dimensional association detection in large scale genomic data

Abstract

Comparisons among experimental results with large amounts of data can be more precise and meaningful when done across multiple different conditions simultaneously. Koch et al. introduce a method, called CLIMB, that does this, and captures interpretable and biologically meaningful information.