On the association analysis of genome-sequencing data: A spatial clustering approach for partitioning the entire genome into nonoverlapping windows

Genetic Epidemiology

Volumn 41, Issue 4, 2017, Pages 332-340

  Loehlein Fier, Heide ^a,b   Prokopenko, Dmitry ^c   Hecker, Julian ^b   Cho, Michael H ^c   Silverman, Edwin K ^c   Weiss, Scott T ^c   Tanzi, Rudolph E ^d   Lange, Christoph ^a,c  

^a HARVARD SCHOOL OF PUBLIC HEALTH   (United States)

^b UNIVERSITY OF BONN   (Germany)

^c HARVARD MEDICAL SCHOOL   (United States)

^d MASSACHUSETTS GENERAL HOSPITAL   (United States)

Author keywords

clustering; genetic association analysis; WGS data

Indexed keywords

ALZHEIMER DISEASE; ARTICLE; FAMILY STUDY; GENE; GENE CLUSTER; GENE LOCUS; GENETIC ALGORITHM; GENETIC ASSOCIATION STUDY; GENETIC SUSCEPTIBILITY; GENETIC VARIABILITY; HUMAN; ITGB3 GENE; SIMULATION; WHOLE GENOME SEQUENCING; ALGORITHM; BIOLOGICAL MODEL; CLUSTER ANALYSIS; COMPUTER SIMULATION; DNA SEQUENCE; GENETICS; GENOME; GENOME-WIDE ASSOCIATION STUDY; GENOMICS; SOFTWARE;

ALGORITHMS; ALZHEIMER DISEASE; CLUSTER ANALYSIS; COMPUTER SIMULATION; GENOME; GENOME-WIDE ASSOCIATION STUDY; GENOMICS; HUMANS; MODELS, GENETIC; SEQUENCE ANALYSIS, DNA; SOFTWARE;

EID: 85016555036     PISSN: 07410395     EISSN: 10982272     Source Type: Journal    
DOI: 10.1002/gepi.22040     Document Type: Article

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