seXY: a tool for sex inference from genotype arrays.
Bioinformatics
; 33(4): 561-563, 2017 02 15.
Article
em En
| MEDLINE
| ID: mdl-28035028
ABSTRACT
Motivation Checking concordance between reported sex and genotype-inferred sex is a crucial quality control measure in genome-wide association studies (GWAS). However, limited insights exist regarding the true accuracy of software that infer sex from genotype array data. Results:
We present seXY, a logistic regression model trained on both X chromosome heterozygosity and Y chromosome missingness, that consistently demonstrated >99.5% sex inference accuracy in cross-validation for 889 males and 5,361 females enrolled in prostate cancer and ovarian cancer GWAS. Compared to PLINK, one of the most popular tools for sex inference in GWAS that assesses only X chromosome heterozygosity, seXY achieved marginally better male classification and 3% more accurate female classification. Availability and Implementation https//github.com/Christopher-Amos-Lab/seXY. Contact Christopher.I.Amos@dartmouth.edu. Supplementary information Supplementary data are available at Bioinformatics online.
Texto completo:
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Base de dados:
MEDLINE
Assunto principal:
Cromossomos Sexuais
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Análise para Determinação do Sexo
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Software
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Cromossomos Humanos
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Estudo de Associação Genômica Ampla
Limite:
Female
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Humans
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Male
Idioma:
En
Ano de publicação:
2017
Tipo de documento:
Article