Skip to content

schnablelab/XP-GWAS

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

5 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

XP-GWAS: a method for identifying trait-associated variants by sequencing pools of individuals

Here we report a method for conducting GWAS that does not require the genotyping of large numbers of individuals. Instead, XP-GWAS (extreme phenotype GWAS) relies on genotyping pools of individuals from a diversity panel having extreme phenotypes. This analysis measures allele frequencies in the extreme pools, enabling the discovery of associations between genetic variants and traits of interest.

INSTALLATION AND USAGE

Clone the repo

git clone [email protected]:yangjl/XP-GWAS.git

Format your input data

Input data should be a tab separated file with the column names matching the below example.

  • Columns 1-3 should be "snpid" (SNP ID), "chr" (Chromosome name) and "pos" (Physical Position).
  • Columns 4 and onwards, with column names like high_ref and high_alt, indicate the reference and alternative allele counts at each polymorphic site.
    snpid chr  pos high_ref high_alt low_ref low_alt random_ref random_alt
1 10_3005  10 3005        0        1       1       7          0          0
2 10_3219  10 3219        5        5       9       5          6          4
3 10_3452  10 3452       26       28      32      92         32         52
4 10_3523  10 3523        4        8       8      27          9         11
5 10_3658  10 3658        9       25      10      18          6         17
6 10_4099  10 4099       12        5      14       3         13         11

Run statistical test for XP-GWAS

The following scripts should be ran in R console. An add-on package GenABEL should be installed first.

install.packages("GenABEL")
source("lib/xpgwas.R")
library("GenABEL")

### read the input data
input <- read.table("data/input_sample.txt", header=TRUE)

### get FDR corrected p-values for sites passed your filtering criterion (DEFAULT filter = 50)
### plotlambda: indicate whether to plot the genomic control results, default = TRUE.
qval <- xpgwas(input, filter=200,  plotlambda=TRUE)

### save results
save(file="cache/qval.RData", list=c("input", "qval"))

Plot your results

source("lib/xpplot.R")
xpplot(qval)

DOCUMENTATION

For more information, see our tutorial.

About

No description, website, or topics provided.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages