Inferring cellular and molecular processes in single-cell data with non-negative matrix factorization using Python, R and GenePattern Notebook implementations of CoGAPS

Non-negative matrix factorization (NMF) is an unsupervised learning method well suited to high-throughput biology. However, inferring biological processes from an NMF result still requires additional post hoc statistics and annotation for interpretation of learned features. Here, we introduce a suit...

Full description

Saved in:
Bibliographic Details
Published in:Nature protocols Vol. 18; no. 12; pp. 3690 - 3731
Main Authors: Johnson, Jeanette A. I., Tsang, Ashley P., Mitchell, Jacob T., Zhou, David L., Bowden, Julia, Davis-Marcisak, Emily, Sherman, Thomas, Liefeld, Ted, Loth, Melanie, Goff, Loyal A., Zimmerman, Jacquelyn W., Kinny-Köster, Ben, Jaffee, Elizabeth M., Tamayo, Pablo, Mesirov, Jill P., Reich, Michael, Fertig, Elana J., Stein-O’Brien, Genevieve L.
Format: Journal Article
Language:English
Published: London Nature Publishing Group UK 01.12.2023
Nature Publishing Group
Subjects:
ISSN:1754-2189, 1750-2799, 1750-2799
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Be the first to leave a comment!
You must be logged in first