test_beta: Hypothesis testing of annotation enrichment

In mingjingsi/LPM: LPM (Latent Probit Model)

Description

Hypothesis testing of annotation enrichment.

Usage

test_beta(data, X, id, LPMfit)
test_beta_louise(data, X, id, LPMfit)

Arguments

data	A list of dataframes which contains SNP IDs and p-values for multiple 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.
id	ID of the target GWAS, the length is 1. For example, id = 1 means we consider the first GWAS in data.
LPMfit	LPM model fit.

Details

test_beta implements the hypothesis testing of annotation enrichment. test_beta_louise implements the hypothesis testing of annotation enrichment using Louise method.

Value

Returns

p_value	p-value of the hypothesis testing of annotation enrichment.
se	Standard error of the estimates beta.

Author(s)

Jingsi Ming

See Also

LPM, test_beta

Examples

data(ExampleData)

result_test_beta <- test_beta(ExampleData$data, X = ExampleData$X, id = 1, LPMfit)

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