FDR made easy in differential feature discovery and correlation analyses

Bioinformatics

Volumn 25, Issue 11, 2009, Pages 1461-1462

  Ling, Xuefeng Bruce ^a   Cohen, Harvey ^a   Jin, Joseph ^a   Lau, Irwin ^a   Schilling, James ^a  

^a STANFORD UNIVERSITY SCHOOL OF MEDICINE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ANALYTICAL ERROR; ARTICLE; CORRELATION ANALYSIS; GENETIC ANALYSIS; GENOMICS; MATHEMATICAL COMPUTING; MEDICAL TECHNOLOGY; PRIORITY JOURNAL; PROTEIN ANALYSIS; PROTEOMICS; STATISTICAL ANALYSIS; SYSTEMS BIOLOGY;

COMPUTATIONAL BIOLOGY; FALSE POSITIVE REACTIONS; GENE EXPRESSION PROFILING; SOFTWARE;

EID: 65649132280     PISSN: 13674803     EISSN: 14602059     Source Type: Journal    
DOI: 10.1093/bioinformatics/btp176     Document Type: Article

References (5)

1. Aubert,J. et al. (2004) Determination of the differentially expressed genes in microarray experiments using local FDR. BMC Bioinformatics, 5, 125.
2. Benjamini,Y. and Hochberg,Y. (1995) Controlling the false discovery rate: A practical and powerful approach to multiple testing. JRSSB 57, 289-300.
3. Efron,B. et al. (2001) Empirical Bayes analysis of microarray experiment. J. Am. Stat. Assoc., 96, 1151-1160.
4. Tusher,V.G. et al. (2001) Significance analysis of microarrays applied to the ionizing radiation response. Proc. Natl Acad. Sci. USA 98, 5116-5121.
5. Westfall,P.H. et al. (1999) Multiple Comparisons and Multiple Tests (Using the SAS System). SAS Institute.