LRpath: a logistic regression approach for identifying enriched biological groups in gene expression data | Zendy

Maureen A. Sartor | Zendy; George D. Leikauf | Zendy; Mario Medvedovic | Zendy

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LRpath: a logistic regression approach for identifying enriched biological groups in gene expression data

Author(s) -

Maureen A. Sartor,

George D. Leikauf,

Mario Medvedovic

Publication year - 2008

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/btn592

Subject(s) - logistic regression , context (archaeology) , statistical hypothesis testing , computer science , statistical power , microarray analysis techniques , data mining , set (abstract data type) , sample size determination , multiple comparisons problem , regression analysis , computational biology , statistics , biology , mathematics , gene , gene expression , machine learning , genetics , paleontology , programming language

The elucidation of biological pathways enriched with differentially expressed genes has become an integral part of the analysis and interpretation of microarray data. Several statistical methods are commonly used in this context, but the question of the optimal approach has still not been resolved.

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