BGWAS: Bayesian variable selection in linear mixed models with nonlocal priors for genome-wide association studies
Abstract Background Genome-wide association studies (GWAS) seek to identify single nucleotide polymorphisms (SNPs) that cause observed phenotypes. However, with highly correlated SNPs, correlated observations, and the number of SNPs being two orders of magnitude larger than the number of observation...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
BMC
2023-05-01
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| Series: | BMC Bioinformatics |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12859-023-05316-x |