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Supplemental Material for Jin et al., 2019

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posted on 2019-05-31, 15:27 authored by Yumi Jin, Alejandro Schaffer, Michael Feolo, J. Bradley Holmes, Brandi Kattman

Figure S1 shows distribution of GRAF-pop scores of subjects with different study-reported, continental populations across all dbGaP studies. Figure S2 shows distribution of GRAF-pop scores of subjects included in 1000 Genomes Project. Table S1 summarizes study-reported populations and the GRAF-calculated populations of dbGaP subjects. Table S2 describes dbGaP studies selected to evaluate GRAF-pop and other ancestry-inference software packages.

History

Article title

GRAF-pop: A Fast Distance-based Method to Infer Subject Ancestry from Multiple Genotype Datasets without Principal Components Analysis

Manuscript #

G3/2018/200925-T

Article DOI

10.1534/g3.118.200925

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GRAF-pop: A Fast Distance-based Method to Infer Subject Ancestry from Multiple Genotype Datasets without Principal Components Analysis

G3: Genes|Genomes|Genetics

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Keywords

Population Structure ancestry inference admixture mapping Genome wide association studies Bioinformatics Population, Ecological and Evolutionary Genetics Genomics Genetics Computational Biology

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