Expanded version of JAM (a single-trait fine-mapping approach) that first runs on thinned SNPs and then expands models on tag SNPs; this can run independently on multiple traits This version is more stable than JAMexpandedCor.multi, but slower, so is run only if JAMexpandedCor.multi fails

Expanded version of JAM (a single-trait fine-mapping approach) that first runs on thinned SNPs and then expands models on tag SNPs; this can run independently on multiple traits This version is more stable than JAMexpandedCor.multi, but slower, so is run only if JAMexpandedCor.multi fails

JAMexpandedCor.multi2(beta1, corX, raf, ybar, Vy, N, r2 = 0.99, save.path)

Arguments

beta1	list where each component is a named vector of of single SNP effect estimates for a trait; one vector for each trait
corX	genotype correlation matrix (reference or from sample)
raf	named vector of reference allele frequencies; the name of each allele frequency is the SNP ID and MUST be in same SNP order as in corX
ybar	vector of trait means; if related samples, this should be based on unrelated samples; if traits are transformed to be standard Normal, could set ybar as 0-vector
Vy	vector of trait variances; if related samples, this should be based on unrelated samples; if traits are transformed to be standard Normal, could set Vy as 1-vector
N	vector of sample sizes for each trait; recommended to give effective sample sizes using GWAS summary statistics in Neff function
r2	r.squared threshold for thinning SNPs before JAM and finding tag SNPs
save.path	path to save JAM output files; tmp files and could delete these later e.g. save.path=paste0(DIRout,"/tmpJAM/region1").

Value

list with 3 components: SM a list of snpmod objects giving fine-mapping results for each trait; mbeta a list of joint effect estimates for each trait; nsnps number of SNPs