mSigHdp: hierarchical Dirichlet process mixture modeling for mutational signature discovery
mSigHdp: hierarchical Dirichlet process mixture modeling for mutational signature discovery
About this item
Full title
Author / Creator
Liu, Mo , Wu, Yang , Jiang, Nanhai , Boot, Arnoud and Rozen, Steven G
Publisher
England: Oxford University Press
Journal title
Language
English
Formats
Publication information
Publisher
England: Oxford University Press
Subjects
More information
Scope and Contents
Contents
Mutational signatures are characteristic patterns of mutations caused by endogenous or exogenous mutational processes. These signatures can be discovered by analyzing mutations in large sets of samples—usually somatic mutations in tumor samples. Most programs for discovering mutational signatures are based on non-negative matrix factorization (NMF)...
Alternative Titles
Full title
mSigHdp: hierarchical Dirichlet process mixture modeling for mutational signature discovery
Authors, Artists and Contributors
Author / Creator
Identifiers
Primary Identifiers
Record Identifier
TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_9869330
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_9869330
Other Identifiers
ISSN
2631-9268
E-ISSN
2631-9268
DOI
10.1093/nargab/lqad005
