Meta-Analysis of Genome Wide Association Studies

Previously we conducted a genome wide association study (GWAS). Genome-wide association studies are useful for detecting common variants in complex diseases. Meta-analysis of multiple genome-wide association studies increases the power of detecting rare variants and reduces false positives.

Today we will conduct a meta-analysis of two previously conducted prostate cancer GWASs in humans.

Download METAL

cd
curl -O http://csg.sph.umich.edu/abecasis/Metal/download/Linux-metal.tar.gz
tar -xvzf Linux-metal.tar.gz 
sudo mv generic-metal/metal /usr/local/bin/.

Download a prostate cancer dataset and unpack

curl -O https://de.cyverse.org/dl/d/9DEF6A65-F0A7-4C6E-8633-957C118FD1B3/meta_GWAS.tar.gz
tar -xvzf meta_GWAS.tar.gz
cd ~/meta_GWAS

Let’s look at each study’s manhattan plot.

** Study1:prostate-606 **

** Study2:prostate-396 **

We may be able to use the power of meta-analysis to resolve some of the questionably significant markers.

Let’s use METAL to run a fixed-effect meta-analysis weighted by sample number fore each study.

Note: it is important to investigate what type of meta-analysis is most appropriate for your study, as each kind has limitations. For example, fixed effect meta-analyses will be biased under a large amount of heterogeneity.

Run metal

Start METAL:

metal

and press enter to access the program.

Next, lets tell METAL what files to read in and a little bit about the files:

# METAL commands
# READ in 606 data
SCHEME STDERR
MARKER SNP_ID
ALLELE Allele.1 Allele.2
EFFECT beta
STDERR SE
PROCESS prostate_606.assoc.logistic

# READ in 733 data
MARKER SNP
ALLELE A1 A2
EFFECT BETA
STDERR SE
PROCESS prostate_396.assoc.logistic

ANALYZE

Now exit the program by typing

quit

and hitting the return key.

We can see our meta-analysis results in the METAANALYSIS1.TBL file.

Visualize Meta-Analysis Results

First, we need to install one more R package RColorBrewer.

sudo Rscript -e "install.packages('RColorBrewer', contriburl=contrib.url('http://cran.r-project.org/'))"

Now we can create a manhattan plot from our results.

Rscript create_manhattan.R METAANALYSIS1.TBL

This will take a minute.

Now lets view our plot in the RStudio server tab!

setwd("/home/tx160085/meta_GWAS")
openPDF("METAANALYSIS1.TBL.allChrs.manhattan.png")