angelovici-lab/happi.gwas

A genome-wide association study (GWAS) tool written in R

HAPPI GWAS

HAPPI GWAS is a genome-wide association study (GWAS) tool written in R.

Installation

You can install the HAPPI.GWAS from Github with:

# Run this inside R environment
install.packages("devtools", dependencies = TRUE)
devtools::install_github("Angelovici-Lab/HAPPI.GWAS")

# Run this in your terminal
mkdir HAPPI_GWAS
cd HAPPI_GWAS
git clone https://github.com/Angelovici-Lab/HAPPI.GWAS.git
cd HAPPI.GWAS
Rscript setup.R

Usage

Rscript HAPPI_GWAS.R [-h] [-generateBLUP] [-generateBLUE] [-GAPIT] [-extractHaplotype] [-searchGenes] input

positional arguments:
  input              Input YAML File

optional arguments:
  -h, --help         show this help message and exit
  -generateBLUP      Generate BLUP data from raw data
  -generateBLUE      Generate BLUE data from raw data
  -GAPIT             Run GAPIT
  -extractHaplotype  Extract haplotype (Require: -GAPIT)
  -searchGenes       Search genes (Require: -GAPIT)

Example

This is a basic example which shows you how to use HAPPI.GWAS:

cd /path/to/HAPPI_GWAS/HAPPI.GWAS
Rscript HAPPI_GWAS.R -GAPIT -extractHaplotype -searchGenes Demo_GLM.yaml
Rscript HAPPI_GWAS.R -GAPIT -extractHaplotype -searchGenes Demo_FarmCPU.yaml

Package Update

To upgrade HAPPI.GWAS to the latest version, please remove the package and re-install the latest HAPPI.GWAS package:

# Run this inside R environment
remove.packages("HAPPI.GWAS")
devtools::install_github("Angelovici-Lab/HAPPI.GWAS")

# Run this in your terminal
cd /path/to/HAPPI_GWAS/HAPPI.GWAS
git pull

Wiki

HAPPI GWAS Wiki Page

User Manual

HAPPI GWAS User Manual

Updates

10-02-2020: Updated the DESCRIPTION file because LDHeatmap was removed from CRAN
05-28-2020: Added HAPPI GWAS user manual
05-16-2020: Added HAPPI GWAS wiki page

happi.gwas's Issues

HAPPI.GWAS results not the same as GAPIT3

Hi,

I've run FarmCPU using the demo data provided using the command below, and run the same analysis using GAPIT within R, matching the same options as the Demo_FarmCPU.yaml file. Though the results are similar, there are in fact some differences.

Using HAPPI GWAS:
Rscript HAPPI_GWAS.R -GAPIT Demo_FarmCPU.yaml

Within R:
library(GAPIT3)
phenos = read.table("mdp_traits.txt", header = TRUE)
myGAPIT <- GAPIT(
Y=phenos,
Model.selection = TRUE,
model=c("FarmCPU"),
SNP.MAF = 0.05,
ncpus = 20,
file.G="mdp_genotype_chr",
file.Ext.G="hmp.txt",
file.from=1,
file.to=10,
file.path="./Demo/"
)

Is there a reason for differences in results if presumably the same model should be being fit?

Thank you,
Jonas