A resource-efficient tool for mixed model association analysis of large-scale data
A resource-efficient tool for mixed model association analysis of large-scale data
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Publisher
New York: Nature Publishing Group US
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Language
English
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Publisher
New York: Nature Publishing Group US
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The genome-wide association study (GWAS) has been widely used as an experimental design to detect associations between genetic variants and a phenotype. Two major confounding factors, population stratification and relatedness, could potentially lead to inflated GWAS test statistics and hence to spurious associations. Mixed linear model (MLM)-based...
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Full title
A resource-efficient tool for mixed model association analysis of large-scale data
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TN_cdi_proquest_miscellaneous_2318733184
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_miscellaneous_2318733184
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ISSN
1061-4036
E-ISSN
1546-1718
DOI
10.1038/s41588-019-0530-8
