GxEScanR: Performs GWAS/GWEIS scans using BinaryDosage files

GxEScanR

GxEScanR is designed to efficiently run genome-wide association study (GWAS) and genome-wide by environmental interaction study (GWEIS) scans using imputed genotypes stored in the BinaryDosage format. The phenotype to be analyzed can either be a continuous or binary trait. The GWEIS scan performs multiple tests that can be used in two-step methods.

Installation

You can install the released version of GxEScanR from CRAN with:

install.packages("GxEScanR")

And the development version from GitHub with:

# install.packages("devtools")
devtools::install_github("USCbiostats/GxEScanR")

Example

The following is a step by step example on how to run a GWAS.

The first step is to load the subject phenotype and covariate data. In this example the data is included with the package. The data is stored in a RDS formatted file. The first five lines of the data frame are shown. The first column is the subject ID, sid. The second column is the phenotype, y. The last column is a covariate,e.

library(GxEScanR)

covdatafile <- system.file("extdata", "covdata.rds", package = "GxEScanR")
covdata <- readRDS(covdatafile)
covdata[1:5,]
#>   sid y e
#> 1  I1 0 0
#> 2  I2 0 0
#> 3  I3 0 0
#> 4  I4 0 0
#> 5  I5 0 0

The second step is to load the information about the binary dosage file. This is obtained by running BinaryDosage::getbdinfo(). More information about this can be found in the BinaryDosage package.

A binary dosage file and information file about it are included with this package. The getbdinfo routine stores the complete file path to the binary dosage file. The installation routine moved the binary dosage from its original location. The third line of code corrects this. The user will not need to run the third line in normal usage.

  bdinfofile <- system.file("extdata", "pdata_4_1.bdinfo", package = "GxEScanR")
  bdinfo <- readRDS(bdinfofile)
  # Not normally run - This is needed only for the example data file
  bdinfo$filename <- system.file("extdata", "pdata_4_1.bdose", package = "GxEScanR")

Everything is now ready to run a GWAS. The number of subjects used in the analysis is displayed at the start of the run. There are a lot of options not being shown in this README file. Information on these options can be found in the documentation and vignettes.

results <- gwas(data = covdata, bdinfo = bdinfo)
#> [1] "200 subjects have complete data"
results
#>       snp      betag      lrtg
#> 1 1:10001  0.7129412 9.0230000
#> 2 1:10002 -0.0943161 0.1219431
#> 3 1:10003 -0.3143876 1.3776592
#> 4 1:10004  0.1397320 0.2356375
#> 5 1:10005  0.2680398 1.2002662

In this example the output was stored in a data frame and displayed. An option exists to output the results to a text file that can easily be read into R using read.table.

The columns in the output are the SNP ID, the coefficient estimate for the genetic effect (betag), and the likelihood ratio test for the estimate (lrtg). The first SNP was simulated with a log odds ratio of 0.75, and the others were simulated to have no effect. The results are consistent with the modelling.