Scalable probabilistic PCA for large-scale genetic variation data.
Principal component analysis (PCA) is a key tool for understanding population structure and controlling for population stratification in genome-wide association studies (GWAS). With the advent of large-scale datasets of genetic variation, there is a need for methods that can compute principal compon...
| الحاوية / القاعدة: | PLoS Genetics |
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| المؤلفون الرئيسيون: | , , , , |
| التنسيق: | مقال |
| اللغة: | الإنجليزية |
| منشور في: |
Public Library of Science (PLoS)
2020-05-01
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| الوصول للمادة أونلاين: | https://doi.org/10.1371/journal.pgen.1008773 |