bLPM_add: Fit bLPM if more GWASs are added

In mingjingsi/LPM: LPM (Latent Probit Model)

Description

Fit bLPM if more GWASs are added.

Usage

bLPM_add(data, data_add, X = NULL, bLPMfit, maxiter = 1e4, tol = 1e-8, coreNum = 1, verbose = FALSE)

Arguments

data	A list of dataframes which contains SNP IDs and p-values for original GWASs, the length is the number of GWASs.
data	A list of dataframes which contains SNP IDs and p-values for added GWASs, the length is the number of GWASs.
X	Design matrix of functional annotations without intercept, where row and column correspond to SNP and annotation, respectively. Default is NULL.
bLPMfit	bLPM fit for original GWASs.
maxiter	Maximum number of EM iteration. Default is 1000.
tol	Threshold to stop the EM iteration. Default is 1e-08.
coreNum	Number of cores used. Default is 1.
verbose	Whether or not to output the estimates of parameters in stage 1 and stage2. Defalut is FALSE.

Details

bLPM_add fits the bLPM when more GWASs are added.

Value

List of parameter estimation, the value of lower bound of Log-likelihood. It has the same form as bLPM.

Author(s)

Jingsi Ming

See Also

bLPM

Examples

data(ExampleData)

bLPMfit <- bLPM(ExampleData$data[1:3], ExampleData$data[4], X = ExampleData$X, bLPMfit_first3, coreNum = 2)

mingjingsi/LPM documentation built on April 2, 2020, 9:32 a.m.