JAM_PointEstimates: JAM (Joint Analysis of Marginal statistics) multivariate...

In pjnewcombe/R2BGLiMS: R interface to the java package BGLiMS (Bayesian Generalised Linear Model Selection).

Description

Constructs a point estimate of multivariate SNP effects, based on the JAM estimator, from a vetorc of marginal effects and a reference genotype matrix.

Constructs a point estimate of multivariate SNP effects, based on the JAM estimator, from a vetorc of marginal effects and a reference genotype matrix.

Usage

JAM_PointEstimates(
  marginal.betas = NULL,
  X.ref = NULL,
  cor.ref = NULL,
  mafs.ref = NULL,
  n = NULL,
  just.get.z = FALSE,
  mafs.if.independent = NULL
)

JAM_PosteriorSampler(marginal.betas = NULL, X.ref = NULL)

Arguments

marginal.betas	Vector of (named) marginal effect estimates to re-analyse with JAM under multivariate models. For multi-ethnic "mJAM" please provide a list of vectors, each element of which is a vector of marginal effects for a specific ethnicity over the same variants.
X.ref	Reference genotype matrix used by JAM to impute the SNP-SNP correlations. If multiple regions are to be analysed this should be a list containing reference genotype matrices for each region. Individual's genotype must be coded as a numeric risk allele count 0/1/2. Non-integer values reflecting imputation may be given. NB: The risk allele coding MUST correspond to that used in marginal.betas. These matrices must each be positive definite and the column names must correspond to the names of the marginal.betas vector.
cor.ref	Alternatively to a reference genotype matrix, a reference correlation matrix AND mafs may be supplied to JAM. NB: The risk allele coding MUST correspond to that used in marginal.betas. These matrices must each be positive definite and the column and row names must correspond to the names of the marginal.betas vector.
mafs.ref	Alternatively to a reference genotype matrix, a reference correlation matrix AND mafs may be supplied to JAM. NB: The risk allele coding MUST correspond to that used in marginal.betas. This must be a named vector with names correspond to the names of the marginal.betas vector.
n	The size of the dataset in which the summary statistics (marginal.betas) were calculated
just.get.z	Return the estimated X'y outcome used in JAM (without actually calculating the corresponding point estimates). This is mainly for internal use.
mafs.if.independent	If the SNPs are independent then a reference genotype matrix is not required. However, it is still necessary to provide SNP MAFs here as a named vector. Doing so will lead to X.ref being ignored and the SNPs to be modelled as if they are independent. Note that this option does not work with enumeration.

Value

A vector of multivariate point estimates.

A vector of multivariate point estimates.

Author(s)

Paul Newcombe

Paul Newcombe

See Also

See also JAM.

See also JAM.

pjnewcombe/R2BGLiMS documentation built on Feb. 10, 2020, 8:52 p.m.