Iterative pruning PCA improves resolution of highly structured populations

BMC Bioinformatics

Volumn 10, Issue , 2009, Pages

  Intarapanich, Apichart ^a   Shaw, Philip J ^b   Assawamakin, Anunchai ^b,c   Wangkumhang, Pongsakorn ^b   Ngamphiw, Chumpol ^b   Chaichoompu, Kridsadakorn ^b   Piriyapongsa, Jittima ^b   Tongsima, Sissades ^b  

^a NATIONAL ELECTRONICS AND COMPUTER TECHNOLOGY CENTER   (Thailand)

^b NATIONAL SCIENCE AND TECHNOLOGY DEVELOPMENT AGENCY   (Thailand)

^c MAHIDOL UNIVERSITY   (Thailand)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONALLY EFFICIENT; EVOLUTIONARY FACTORS; GENETIC VARIATION; NON-RANDOM PATTERNS; POPULATION STRUCTURES; PRINCIPAL COMPONENTS ANALYSIS; SIMPLE STRUCTURES; STRUCTURED POPULATION;

ALGORITHMS; COMPUTATIONAL EFFICIENCY; GENES; ITERATIVE METHODS; PRINCIPAL COMPONENT ANALYSIS;

POPULATION STATISTICS;

PREGNANCY ASSOCIATED ALPHA2 GLYCOPROTEIN; PREGNANCY SPECIFIC BETA1 GLYCOPROTEIN;

ARTICLE; ETHNICITY; GENE CLUSTER; GENE FREQUENCY; GENE LOCUS; GENE MAPPING; GENE STRUCTURE; GENETIC DATABASE; GENOTYPE; HETEROZYGOSITY; HOMOZYGOSITY; ITERATIVE PRUNING PRINCIPAL COMPONENT ANALYSIS; POPULATION STRUCTURE; PRINCIPAL COMPONENT ANALYSIS; PROTEIN DOMAIN; SIMULATION; SINGLE NUCLEOTIDE POLYMORPHISM; STRATIFICATION; STRUCTURE ANALYSIS; ALGORITHM; ANIMAL; BIOLOGICAL MODEL; BIOLOGY; GENETIC VARIABILITY; GENETICS; HUMAN; METHODOLOGY; POPULATION; POPULATION GENETICS;

ALGORITHMS; ANIMALS; COMPUTATIONAL BIOLOGY; GENETIC VARIATION; GENETICS, POPULATION; HUMANS; MODELS, GENETIC; POPULATION; PRINCIPAL COMPONENT ANALYSIS;

EID: 71949111362     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/1471-2105-10-382     Document Type: Article

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