Cancer outlier detection based on likelihood ratio test | Zendy

Jianhua Hu | Zendy

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Cancer outlier detection based on likelihood ratio test

Author(s) -

Jianhua Hu

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/btn372

Subject(s) - outlier , r package , computer science , relevance (law) , statistical power , statistical hypothesis testing , data mining , cancer , microarray analysis techniques , likelihood ratio test , false discovery rate , artificial intelligence , pattern recognition (psychology) , statistics , mathematics , biology , gene , gene expression , computational science , political science , law , genetics , biochemistry

Microarray experiments can be used to help study the role of chromosomal translocation in cancer development through cancer outlier detection. The aim is to identify genes that are up- or down-regulated in a subset of cancer samples in comparison to normal samples.

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