Package: GxEprs 1.2

GxEprs: Genotype-by-Environment Interaction in Polygenic Score Models

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) <doi:10.1093/annonc/mdu565>, (Pandis et al., 2013) <doi:10.1093/ejo/cjt054>, (Peyrot et al., 2018) <doi:10.1016/j.biopsych.2017.09.009> and (Song et al., 2022) <doi:10.1038/s41467-022-32407-9>, as well as newly proposed models for genomic risk prediction (refer to the URL for more details).

Authors:Dovini Jayasinghe [aut, cre, cph], Hong Lee [aut, cph], Moksedul Momin [aut, cph]

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GxEprs.pdf |GxEprs.html✨
GxEprs/json (API)

# Install 'GxEprs' in R:
install.packages('GxEprs', repos = c('https://dovinij.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/dovinij/gxeprs/issues

Datasets:
  • 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.
  • 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.
  • DummyData.bim - PLINK .bim file
  • DummyData.fam - PLINK .fam file
  • DummyData.map - PLINK .map file
  • DummyData.ped - PLINK .ped file
  • 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.
  • 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.
  • 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.
  • 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.

On CRAN:

10 exports 2 stars 1.38 score 0 dependencies 905 downloads

Last updated 4 months agofrom:f4395d5441. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKAug 27 2024
R-4.5-winOKAug 27 2024
R-4.5-linuxOKAug 27 2024
R-4.4-winOKAug 27 2024
R-4.4-macOKAug 27 2024
R-4.3-winOKAug 27 2024
R-4.3-macOKAug 27 2024

Exports:GWAS_binaryGWAS_quantitativeGWEIS_binaryGWEIS_quantitativePRS_binaryPRS_quantitativesummary_permuted_binarysummary_permuted_quantitativesummary_regular_binarysummary_regular_quantitative

Dependencies:

Readme and manuals

Help Manual

Help pageTopics
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.Bcov_discovery
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.Bcov_target
Phenotype data file of the discovery dataset when the outcome is binary. This contains phenotype information of the individuals in the discovery dataset.Bphe_discovery
Phenotype data file of the target dataset when the outcome is binary. This contains phenotype information of the individuals in the target dataset.Bphe_target
PLINK .bim fileDummyData.bim
PLINK .fam fileDummyData.fam
PLINK .map fileDummyData.map
PLINK .ped fileDummyData.ped
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).GWAS_binary
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).GWAS_quantitative
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).GWEIS_binary
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_quantitative
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).PRS_binary
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_quantitative
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.Qcov_discovery
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_target
Phenotype data file of the discovery dataset when the outcome is quantitative. This contains phenotype information of the individuals in the discovery dataset.Qphe_discovery
Phenotype data file of the target dataset when the outcome is quantitative. This contains phenotype information of the individuals in the target dataset.Qphe_target
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_permuted_binary
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).summary_permuted_quantitative
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_binary
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.summary_regular_quantitative