Simultaneous modeling of disease status and clinical phenotypes to increase power in GWAS

pyslmGWAS, a method method for simultaneous association testing of genetic variants with both case status and a clinical covariate that resolves both of these issues.

Tutorial

Usage: python pyslmGWAS.py --tfile plinkFile --f population_frequency --phenofile plinkFormattedPhenotypeFile resultFile (result file should be indicated in the command line) Get beta1, beta2 estimation from bincontmodel.

Options: -v, --verbose Print extra info

--tfile the base for a PLINK tped file

--phenofile phenofile which contains continual phenotypes and discrete disease status if you do not set the parameters, it would automatically search the file whose name starts with the base for a PLINK tped file, and ends with ".phenos"

--f the population frequency

Here is the toy example to show how to run the program

$ python pyslmGWAS.py -v --tfile ./data/simulate --f 0.5 ./data/test.output.txt

Simulation

I also provide the simulation script to further validation our methods.

Usage: python creatSimulateData.py --power 0.5 --n 5000 --f 0.4 --maf 0.2 --base ./data/simulate --cor 0.2 --ez 0.3

--power The power you want to set based on univariate test

--n The total number of case and control studies

--f The population frequency

--maf Minor Allele Frequency

--base The file base for simulation data

--cor The correlation of phenotypes data and disease liability

--ez The effect size of phenotypes on SNPs

$ python creatSimulateData.py --power 0.5 --n 5000 --f 0.4 --maf 0.2 --base ./data/simulate --cor 0.2 --ez 0.3