Expanded version of JAM (a single-trait fine-mapping approach) that first runs on thinned SNPs and then expands models on tag SNPs This version starts at a low upper bound for max causal variants and decides on max upper bound based on data

Expanded version of JAM (a single-trait fine-mapping approach) that first runs on thinned SNPs and then expands models on tag SNPs This version starts at a low upper bound for max causal variants and decides on max upper bound based on data

JAMdynamic(
  gwas,
  corX,
  ybar = 0,
  Vy = 1,
  N,
  cred = 0.99,
  save.path,
  maxcv = 1,
  maxcv_stop = 20,
  jam.nM.iter = 1,
  extra.java.arguments = NULL
)

Arguments

gwas

data.frame with 3 columns named: rsID, beta, EAF

corX

genotype correlation matrix (reference or from sample)

ybar

trait mean; if trait is transformed to be standard Normal, set ybar = 0, which is default

Vy

trait variance; if trait is transformed to be standard Normal, set Vy = 1, which is default

N

sample size for trait; recommended to give effective sample sizes using GWAS summary statistics in Neff function

cred

probability for credible set; default is 0.99

save.path

path to save JAM output files; tmp files and could delete these later e.g. save.path=paste0(DIRout,"/tmpJAM/region1").

maxcv

starting value for maximum number of causal variants

maxcv_stop

maximum value to consider for maximum number of causal variants; maxcv_stop >= maxcv.

jam.nM.iter

in millions, number of iterations to use in JAM; defailt 1 (1 million)

extra.java.arguments

A character string to be passed through to the java command line. E.g. to specify a different temporary directory by passing "-Djava.io.tmpdir=/Temp".

Value

List of credible set variants with their MPP, MPP for all variants, PP for all models

Author

Feng Zhou