This data set contains a genotype matrix for 574 individuals and 1,002 variables. The variables are genotypes after centering and scaling, and therefore retain the correlation structure of the original genotype data. Two of the variables have non-zero effects on the multivariate response. The response data are generated under a multivariate linear regression model. See Wang et al (2020) for details.
N2finemapping is a list with the following elements:
Centered and scaled genotype data.
Chromomsome of the original data, in hg38 coordinates.
Chromomosomal position of the original data, in hg38
coordinates. The information can be used to compare impact of using
other genotype references of the same variables in susie_rss
application.
Simulated effect sizes.
Simulated residual covariance matrix.
Simulated multivariate response.
Allele frequencies based on the original genotype data.
Suggested prior covariance matrix for effect sizes of the two non-zero effect variables.
G. Wang, A. Sarkar, P. Carbonetto and M. Stephens (2020). A simple new approach to variable selection in regression, with application to genetic fine-mapping. Journal of the Royal Statistical Society, Series B https://doi.org/10.1101/501114.
data(N2finemapping)