A loop-counting method for covariate-corrected low-rank biclustering of gene-expression and genome-wide association study data.

A loop-counting method for covariate-corrected low-rank biclustering of gene-expression and genome-wide association study data.

A common goal in data-analysis is to sift through a large data-matrix and detect any significant submatrices (i.e., biclusters) that have a low numerical rank. We present a simple algorithm for tackling this biclustering problem. Our algorithm accumulates information about 2-by-2 submatrices (i.e.,...

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Main Authors: Aaditya V Rangan, Caroline C McGrouther, John Kelsoe, Nicholas Schork, Eli Stahl, Qian Zhu, Arjun Krishnan, Vicky Yao, Olga Troyanskaya, Seda Bilaloglu, Preeti Raghavan, Sarah Bergen, Anders Jureus, Mikael Landen, Bipolar Disorders Working Group of the Psychiatric Genomics Consortium
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2018-05-01
Series:PLoS Computational Biology
Online Access:https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1006105&type=printable
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https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1006105&type=printable

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