A generalized likelihood ratio test to identify differentially expressed genes from microarray data | Zendy

Song Wang | Zendy; S. N. Ethier | Zendy

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A generalized likelihood ratio test to identify differentially expressed genes from microarray data

Author(s) -

Song Wang,

S. N. Ethier

Publication year - 2003

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/btg384

Subject(s) - likelihood ratio test , microarray analysis techniques , microarray , microarray databases , computational biology , test (biology) , gene , biology , computer science , genetics , statistics , gene expression , mathematics , paleontology

Microarray technology emerges as a powerful tool in life science. One major application of microarray technology is to identify differentially expressed genes under various conditions. Currently, the statistical methods to analyze microarray data are generally unsatisfactory, mainly due to the lack of understanding of the distribution and error structure of microarray data.

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