Effective filtering strategies to improve data quality from population-based whole exome sequencing studies

BMC Nephrology

Volumn 15, Issue 1, 2014, Pages

  Carson, Andrew R ^a   Smith, Erin N ^a   Matsui, Hiroko ^a   Brækkan, Sigrid K ^b,c   Jepsen, Kristen ^a   Hansen, John Bjarne ^b,c   Frazer, Kelly A ^a,b,d,e  

^a UNIVERSITY OF CALIFORNIA SAN DIEGO   (United States)

^b UNIVERSITY OF TROMSØ   (Norway)

^c UNIVERSITY HOSPITAL OF NORTH NORWAY   (Norway)

^d UNIVERSITY OF CALIFORNIA   (United States)

^e UNIVERSITY OF CALIFORNIA SAN DIEGO   (United States)

Author keywords

Genomics; Genotyping; Imputation; Next generation sequencing; Single nucleotide variants

Indexed keywords

ACCURACY; ARTICLE; CONTROLLED STUDY; DATA QUALITY; EXOME; FILTRATION; GENE SEQUENCE; GENETIC ASSOCIATION; GENETIC VARIABILITY; GENOME ANALYSIS; GENOTYPE; HUMAN; INFORMATION PROCESSING; NORMAL HUMAN; POPULATION BASED CASE CONTROL STUDY; SENSITIVITY AND SPECIFICITY; TOTAL QUALITY MANAGEMENT; DNA SEQUENCE; HIGH THROUGHPUT SEQUENCING; METHODOLOGY; SINGLE NUCLEOTIDE POLYMORPHISM; STANDARD;

ERRORS; TOOLS;

GENOMICS; GENOTYPING; IMPUTATION; NEXT-GENERATION SEQUENCING; SINGLE NUCLEOTIDES;

POPULATION STATISTICS;

EXOME; GENOTYPE; HIGH-THROUGHPUT NUCLEOTIDE SEQUENCING; HUMANS; POLYMORPHISM, SINGLE NUCLEOTIDE; SEQUENCE ANALYSIS, DNA;

EID: 84899998871     PISSN: None     EISSN: 14712369     Source Type: Journal    
DOI: 10.1186/1471-2105-15-125     Document Type: Article

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