GxEprs (version 1.1)

summary_regular_binary: summary_regular_binary function This function outputs the summary of regular model and final risk score values of each individual in the target dataset using pre-generated Polygenic Risk Scores (PRSs) of all the individuals. Note that the input used in this function can be generated by using PRS_binary function.

Description

summary_regular_binary function This function outputs the summary of regular model and final risk score values of each individual in the target dataset using pre-generated Polygenic Risk Scores (PRSs) of all the individuals. Note that the input used in this function can be generated by using PRS_binary function.

Usage

summary_regular_binary(
  Bphe_target,
  Bcov_target,
  add_score = NULL,
  gxe_score = NULL,
  Model
)

Value

This function will output

Bsummary

the summary of the fitted model

Individual_risk_values

the estimated risk values of individuals in the target sample

Arguments

Bphe_target

Phenotype file containing family ID, individual ID and phenotype of the target dataset as columns, without heading

Bcov_target

Covariate file containing family ID, individual ID, standardized covariate, square of standardized covariate, and/or confounders of the target dataset as columns, without heading

add_score

PRSs generated using additive SNP effects of GWAS/GWEIS summary statistics

gxe_score

PRSs generated using interaction SNP effects of GWEIS summary statistics

Model

Specify the model number (0: y = PRS_trd + E + confounders, 1: y = PRS_trd + E + PRS_trd x E + confounders, 2: y = PRS_add + E + PRS_add x E + confounders, 3: y = PRS_add + E + PRS_gxe x E + confounders, 4: y = PRS_add + E + PRS_gxe + PRS_gxe x E + confounders, 5: y = PRS_add + E + E^2 + PRS_gxe + PRS_gxe x E + confounders, where y is the outcome variable, E is the covariate of interest, PRS_trd and PRS_add are the polygenic risk scores computed using additive SNP effects of GWAS and GWEIS summary statistics respectively, and PRS_gxe is the polygenic risk scores computed using GxE interaction SNP effects of GWEIS summary statistics.)

Examples

if (FALSE) { 
a <- GWAS_binary(plink_path, DummyData, Bphe_discovery, Bcov_discovery)
trd <- a[c("ID", "A1", "OR")]
b <- GWEIS_binary(plink_path, DummyData, Bphe_discovery, Bcov_discovery)
add <- b[c("ID", "A1", "ADD_OR")]
gxe <- b[c("ID", "A1", "INTERACTION_OR")]
p <- PRS_binary(plink_path, DummyData, summary_input = trd)
q <- PRS_binary(plink_path, DummyData, summary_input = add)
r <- PRS_binary(plink_path, DummyData, summary_input = gxe)
summary_regular_binary(Bphe_target, Bcov_target, 
                            add_score = p,
                            Model = 0)
summary_regular_binary(Bphe_target, Bcov_target, 
                            add_score = p,
                            Model = 1)
summary_regular_binary(Bphe_target, Bcov_target, 
                            add_score = q,
                            Model = 2)
summary_regular_binary(Bphe_target, Bcov_target, 
                            add_score = q, 
                            gxe_score = r, 
                            Model = 3) 
summary_regular_binary(Bphe_target, Bcov_target, 
                            add_score = q, 
                            gxe_score = r, 
                            Model = 4) 
x <- summary_regular_binary(Bphe_target, Bcov_target, 
                            add_score = q, 
                            gxe_score = r, 
                            Model = 5) 
sink("Bsummary.txt") #to create a file in the working directory
print(x$summary) #to write the output
sink() #to save the output
sink("Individual_risk_values.txt") #to create a file in the working directory
write.table(x$risk.values, sep = " ", row.names = FALSE, col.names = FALSE, 
quote = FALSE) #to write the output
sink() #to save the output
x$summary #to obtain the model summary output
x$risk.values #to obtain the predicted risk values of target individuals
}