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.,...

Descripción completa

Detalles Bibliográficos
Autores principales: Rangan, Aaditya V., McGrouther, Caroline C., Kelsoe, John, Schork, Nicholas, Stahl, Eli, Zhu, Qian, Krishnan, Arjun, Yao, Vicky, Troyanskaya, Olga, Bilaloglu, Seda, Raghavan, Preeti, Bergen, Sarah, Jureus, Anders, Landen, Mikael
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2018
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5997363/
https://www.ncbi.nlm.nih.gov/pubmed/29758032
http://dx.doi.org/10.1371/journal.pcbi.1006105

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5997363/
https://www.ncbi.nlm.nih.gov/pubmed/29758032
http://dx.doi.org/10.1371/journal.pcbi.1006105

Ejemplares similares