Increased proportion of variance explained and prediction accuracy of survival of breast cancer patients with use of whole-genome multiomic profiles

Genetics

Volumn 203, Issue 3, 2016, Pages 1425-1438

  Vazquez, Ana I ^a   Veturi, Yogasudha ^b   Behring, Michael ^b   Shrestha, Sadeep ^b   Kirst, Matias ^c   Resende, Marcio F R ^c   de los Campos, Gustavo ^a,d  

^a MICHIGAN STATE UNIVERSITY   (United States)

^b UNIVERSITY OF ALABAMA AT BIRMINGHAM   (United States)

^c UNIVERSITY OF FLORIDA   (United States)

^d MICHIGAN STATE UNIVERSITY   (United States)

Author keywords

Diseases risk; Genomic selection; GenPred; Omics integration; Prediction of complex traits; Shared data resource

Indexed keywords

ACCURACY; ADULT; ARTICLE; BAYES THEOREM; BREAST CANCER; CANCER PATIENT; CANCER SURVIVAL; CLINICAL PRACTICE; COMPUTER PREDICTION; COMPUTER PROGRAM; CONTROLLED STUDY; FEMALE; GENE EXPRESSION PROFILING; GENETIC VARIABILITY; HUMAN; MAJOR CLINICAL STUDY; MALE; METHYLATION; ONCOGENE; PRIORITY JOURNAL; RISK ASSESSMENT; WHOLE GENOME MULTIOMIC PROFILE; BIOLOGICAL MODEL; BIOSYNTHESIS; BREAST NEOPLASMS; DISEASE COURSE; DNA METHYLATION; GENE EXPRESSION REGULATION; GENETICS; GENOMICS; HUMAN GENOME; PATHOLOGY; PROTEOMICS; SOFTWARE; SURVIVAL ANALYSIS;

TUMOR PROTEIN;

BREAST NEOPLASMS; DISEASE PROGRESSION; DNA METHYLATION; FEMALE; GENE EXPRESSION REGULATION, NEOPLASTIC; GENOME, HUMAN; GENOMICS; HUMANS; MODELS, GENETIC; NEOPLASM PROTEINS; PROTEOMICS; SOFTWARE; SURVIVAL ANALYSIS;

EID: 84979935404     PISSN: 00166731     EISSN: 19432631     Source Type: Journal    
DOI: 10.1534/genetics.115.185181     Document Type: Article

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