Joint modeling of genetically correlated diseases and functional annotations increases accuracy of polygenic risk prediction

PLoS Genetics

Volumn 13, Issue 6, 2017, Pages

  Hu, Yiming ^a   Lu, Qiongshi ^a   Liu, Wei ^b   Zhang, Yuhua ^c   Li, Mo ^a   Zhao, Hongyu ^a,d,e  

^a YALE UNIVERSITY   (United States)

^b PEKING UNIVERSITY   (China)

^c SHANGHAI JIAO TONG UNIVERSITY   (China)

^d YALE UNIVERSITY SCHOOL OF MEDICINE   (United States)

^e VA CONNECTICUT HEALTHCARE SYSTEM   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ACCURACY; ARTICLE; CELIAC DISEASE; CROHN DISEASE; EFFECT SIZE; GENE LINKAGE DISEQUILIBRIUM; GENETIC DISORDER; GENETIC RISK; GENOME-WIDE ASSOCIATION STUDY; HEREDITY; HUMAN; NON INSULIN DEPENDENT DIABETES MELLITUS; PREDICTION; RISK ASSESSMENT; SIMULATION; BIOLOGICAL MODEL; GENETICS; GENOTYPE; MULTIFACTORIAL INHERITANCE; PHENOTYPE; RISK FACTOR; SINGLE NUCLEOTIDE POLYMORPHISM;

GENETIC DISEASES, INBORN; GENOME-WIDE ASSOCIATION STUDY; GENOTYPE; HUMANS; LINKAGE DISEQUILIBRIUM; MODELS, GENETIC; MULTIFACTORIAL INHERITANCE; PHENOTYPE; POLYMORPHISM, SINGLE NUCLEOTIDE; RISK FACTORS;

EID: 85021818746     PISSN: 15537390     EISSN: 15537404     Source Type: Journal    
DOI: 10.1371/journal.pgen.1006836     Document Type: Article

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