Detecting differentially methylated loci for multiple treatments based on high-throughput methylation data

BMC Bioinformatics

Volumn 15, Issue 1, 2014, Pages

  Chen, Zhongxue ^a   Huang, Hanwen ^b   Liu, Qingzhong ^c  

^a INDIANA UNIVERSITY   (United States)

^b UNIVERSITY OF GEORGIA   (United States)

^c SAM HOUSTON STATE UNIVERSITY   (United States)

Author keywords

Cuzick test; Nonparametric test; Trend test

Indexed keywords

GENE EXPRESSION; METHYLATION; NORMAL DISTRIBUTION;

BIOLOGICAL PROCESS; CASE-CONTROL STUDY; DISEASE DEVELOPMENT; HIGH-THROUGHPUT; NON-PARAMETRIC TEST; NONPARAMETRIC METHODS; STATISTICAL APPROACH; TREND TESTS;

ALKYLATION;

ARTICLE; CASE CONTROL STUDY; DNA METHYLATION; DNA MICROARRAY; FEMALE; GENE LOCUS; GENETICS; HUMAN; NONPARAMETRIC TEST; OVARY TUMOR;

CASE-CONTROL STUDIES; DNA METHYLATION; FEMALE; GENETIC LOCI; HUMANS; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS; OVARIAN NEOPLASMS; STATISTICS, NONPARAMETRIC;

EID: 84900840540     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/1471-2105-15-142     Document Type: Article

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