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KLFDAPC: A Supervised Machine Learning Approach for Spatial Genetic Structure Analysis

2021-05-17

Abstract excerpt

Geographic patterns of human genetic variation provide important insights into human evolution and disease. A commonly used tool to detect geographic patterns from genetic data is principal components analysis (PCA) or the supervised linear discriminant analysis of principal components (DAPC). However, genetic features produced from both approaches could fail to correctly characterize population structure for comp...

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Literature Corpus work
262342bb-132c-54fa-bd2d-197b31200ecb
DOI
10.1101/2021.05.15.444294
Open publication

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KLFDAPC: A Supervised Machine Learning Approach for Spatial Genetic Structure AnalysisDOI 10.1101/2021.05.15.444294
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