A Bayesian multinomial stochastic search with a sharing scale parameter is used to identify the best SNP models for each trait. The sharing scale is used in the joint prior probabilities to give higher weight to joint models that have at least one shared variant between the traits. The best SNP models are summarised in terms of sets of correlated SNPs that have a similar impact on the trait. This approach is an extension of the GUESSFM software for fine-mapping of single traits and relies on several of the functions from that software.
|Maintainer||Jenn Asimit <[email protected]>|
|Package repository||View on GitHub|
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