Open AccessPROMISE: a tool to identify genomic features with a specific biologically interesting pattern of associations with multiple endpoint variables
Author(s) -
Stanley Pounds,
Cheng Cheng,
Xueyuan Cao,
Kristine R. Crews,
William Plunkett,
Varsha Gandhi,
Jeffrey E. Rubnitz,
Raul C. Ribeiro,
James R. Downing,
Jatinder K. Lamba
Publication year - 2009
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btp357
Subject(s) - computational biology , computer science , biology
In some applications, prior biological knowledge can be used to define a specific pattern of association of multiple endpoint variables with a genomic variable that is biologically most interesting. However, to our knowledge, there is no statistical procedure designed to detect specific patterns of association with multiple endpoint variables.