README.md

a_johansson_2020

AJ partner project 2020

Lifecycle: maturing Codecov test coverage R build status build-and-push-to-DockerHub

Objectives

To develop an R package for testing the scope of applicability of different GWA methodologies, esp. with respect to varying: threshold between rare and common variants, the degree of contribution (effect size and direction) contributed by rare and common variants, degree of population structure, varying amount of contributing loci.

Using on Bianca

To use the package on Bianca: the gwasim package is automatically built into a docker container upon every push, container is called gwasim-latest and is stored in quiestrho account on DockerHub, ssh to Rackham, do singularity pull --docker-login docker://quiestrho/gwasim:latest transfer the gwasim_latest.sif file into Bianca's wharf via sftp, move the file from wharf to your project library, singularity exec gwasim_latest.sif R --vanilla < script.r to run an R script within the container

Input

The following input parameters are expected from the user: a VCF file with variants coming from a population under studies, a bed file containing a list of functional regions (e.g. gene list) along with their coordinates, a minor allele frequency threshold for cut-off between rare and common variants, the number of rare and common variants that contribute, distribution of effect sizes as a function of allele frequency (separately for the rare and the common alleles), percentage of alleles with negative effect (for both the common and the rare variants), parameters (mean, standard deviation) of the error term, type of the trait (continuous or binary, a cut-off value for the binary trait),

To add in future:

Output

Documentation

Possible applications:

  1. To validate sensitivity and specificity of various GWA algorithms in the landscape of varying effect sizes, directionalities and mafs.



NBISweden/a_johansson_2020 documentation built on April 18, 2021, 1:09 a.m.