flashfm.input: Key input for flashfm - constructs snpmod object list and...
In jennasimit/flashfm: flexible and shared information fine-mapping

flashfm.input

R Documentation

Key input for flashfm - constructs snpmod object list and joint effect estimates list for all trait if have external single trait fine-mapping results

Description

Key input for flashfm - constructs snpmod object list and joint effect estimates list for all trait if have external single trait fine-mapping results

Usage

flashfm.input(
  modPP.list,
  beta1.list,
  Gmat,
  Nall,
  ybar.all,
  related = FALSE,
  y = NULL,
  Nsame = NULL,
  is.snpmat,
  raf = NULL
)

Arguments

`modPP.list`	list of data.frame objects for each trait, containing a column named "snps": snp models of the form `"snp1,snp2"` and "PP": snp model posterior probabliity from single trait fine-mapping
`beta1.list`	list of single SNP effect estimates for each trait in the form of a named vector; name of each effect estimate should appear in Gmat
`Gmat`	genotype matrix with SNP columns; could be from sample or reference panel; use unrelated samples
`Nall`	vector of sample sizes; if related samples then give effective sample sizes
`ybar.all`	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
`related`	logical indicating if samples are related (TRUE) or not (FALSE); default is FALSE
`y`	(optional) matrix of trait values (trait columns) or indicators of trait measured; used to get joint sample counts; default is NULL and if not provided an approximation is used based on vector of trait sample sizes
`Nsame`	(optional) single sample size value, if all traits measured on all individuals
`is.snpmat`	logical taking value TRUE when Gmat is a genotype matrix and FALSE when Gmat is a SNP covariance matrix
`raf`	named vector of SNP reference allele frequencies where name is snp id (must match SNP coding used for effect estimates); only needed if Gmat is a covariance matrix and MUST be in same order ans snps in covariance matrix