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GxEprs (version 1.1)

Genotype-by-Environment Interaction in Polygenic Score Models

Description

A novel PRS model is introduced to enhance the prediction accuracy by utilising GxE effects. This package performs Genome Wide Association Studies (GWAS) and Genome Wide Environment Interaction Studies (GWEIS) using a discovery dataset. The package has the ability to obtain polygenic risk scores (PRSs) for a target sample. Finally it predicts the risk values of each individual in the target sample. Users have the choice of using existing models (Li et al., 2015) , (Pandis et al., 2013) , (Peyrot et al., 2018) and (Song et al., 2022) , as well as newly proposed models for genomic risk prediction (refer to the URL for more details).

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install.packages('GxEprs')

Monthly Downloads

621

Version

1.1

License

GPL (>= 3)

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Maintainer

Dovini Jayasinghe

Last Published

October 3rd, 2023

Functions in GxEprs (1.1)

PRS_quantitative

PRS_quantitative function This function uses plink2 and outputs Polygenic Risk Scores (PRSs) of all the individuals, using pre-generated GWAS and/or GWEIS summary statistics. Note that the input used in this function can be generated by using GWAS_quantitative and/or GWEIS_quantitative functions. Users may save the output in a user-specified file (see examples).
PRS_binary

PRS_binary function This function uses plink2 and outputs Polygenic Risk Scores (PRSs) of all the individuals, using pre-generated GWAS and/or GWEIS summary statistics. Note that the input used in this function can be generated by using GWAS_binary and/or GWEIS_binary functions. Users may save the output in a user-specified file (see examples).
summary_permuted_quantitative

summary_permuted_quantitative function This function outputs the p value of permuted model 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_quantitative functions. It is recommended to run this function, if you choose to fit 'PRS_gxe x E' interaction component (i.e. novel proposed model, Model 4) when generating risk scores. If the 'PRS_gxe x E' term is significant in Model 4, and insignificant in Model 4* (permuted p value), consider that the 'PRS_gxe x E' interaction component is actually insignificant (always give priority to the p value obtained from the permuted model).
Qphe_discovery

Phenotype data file of the discovery dataset when the outcome is quantitative. This contains phenotype information of the individuals in the discovery dataset.
Qcov_target

Covariate data file of the target dataset when the outcome is quantitative. This contains covariate information of the individuals in the target dataset following confounders.
Qcov_discovery

Covariate data file of the discovery dataset when the outcome is quantitative. This contains covariate information of the individuals in the discovery dataset following confounders.
Qphe_target

Phenotype data file of the target dataset when the outcome is quantitative. This contains phenotype information of the individuals in the target dataset.
summary_permuted_binary

summary_permuted_binary function This function outputs the p value of permuted model 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_quantitative function. It is recommended to run this function, if you choose to fit 'PRS_gxe x E' interaction component (i.e. novel proposed model, Model 5) when generating risk scores. If the 'PRS_gxe x E' term is significant in Model 5, and insignificant in Model 5* (permuted p value), consider that the 'PRS_gxe x E' interaction component is actually insignificant (always give priority to the p value obtained from the permuted model).
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.
summary_regular_quantitative

summary_regular_quantitative 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_quantitative function.
DummyData.fam

PLINK .fam file
GWAS_binary

GWAS_binary function This function performs GWAS using plink2 and outputs the GWAS summary statistics with additive SNP effects. Users may save the output in a user-specified file (see example).
Bcov_target

Covariate data file of the target dataset when the outcome is binary. This contains covariate information of the individuals in the target dataset following confounders.
Bphe_discovery

Phenotype data file of the discovery dataset when the outcome is binary. This contains phenotype information of the individuals in the discovery dataset.
Bphe_target

Phenotype data file of the target dataset when the outcome is binary. This contains phenotype information of the individuals in the target dataset.
GWAS_quantitative

GWAS_quantitative function This function performs GWAS using plink2 and outputs the GWAS summary statistics with additive SNP effects. Users may save the output in a user-specified file (see example).
DummyData.bim

PLINK .bim file
DummyData.map

PLINK .map file
Bcov_discovery

Covariate data file of the discovery dataset when the outcome is binary. This contains covariate information of the individuals in the discovery dataset following confounders.
DummyData.ped

PLINK .ped file
GWEIS_quantitative

GWEIS_quantitative function This function performs GWEIS using plink2 and outputs the GWEIS summary statistics with additive SNP effects and interaction SNP effects separately. It is recommended to save the outputs in separate user-specified files (see examples).
GWEIS_binary

GWEIS_binary function This function performs GWEIS using plink2 and outputs the GWEIS summary statistics with additive SNP effects and interaction SNP effects. Users may save the outputs in separate user-specified files (see examples).