Description
Genome-Wide Association Study with SLOPE.
Description
Genome-wide association study (GWAS) performed with SLOPE, short for Sorted L-One Penalized Estimation, a method for estimating the vector of coefficients in a linear model. In the first step of GWAS, single nucleotide polymorphisms (SNPs) are clumped according to their correlations and distances. Then, SLOPE is performed on the data where each clump has one representative. Malgorzata Bogdan, Ewout van den Berg, Chiara Sabatti, Weijie Su and Emmanuel Candes (2014) "SLOPE - Adaptive Variable Selection via Convex Optimization" <arXiv:1407.3824>.
README.md
geneSLOPE -- Genome Wide Association Study with SLOPE
Package geneSLOPE can be used to perform Genome-wide association study with SLOPE.
Such an analysis is split into three steps.
- Data is read and immediately screened using a marginal test for each SNP.
- SNPs are clumped based on correlations.
- SLOPE is performed on reduced data. Each clump is represented by one SNP.
How do I get set up?
You can install the latest development version of the code using the devtools R package.
# Install devtools, if you haven't already.
install.packages("devtools")
library(devtools)
install_github("psobczyk/geneSLOPE")
- You might need to install package dependencies:
- SLOPE
- ggplot2
- bigmemory
- grid
- Read vignette "Tutorial for GWAS with SLOPE" to get familiar with basic usage
Running GUI
GUI based on shiny R package is available
library(geneSLOPE)
gui_geneSLOPE()
Who do I talk to?
- If help provided in the package documentation does not solve your problem please contact Piotr.Sobczyk[at]pwr.edu.pl
Research reported in this software was supported by National Institutes of Health under award number R01 HG006695.
This project has received funding from the European Union’s Seventh Framework Programme for research, technological development and demonstration under grant agreement no 602552.