Genome-wide association (GWA) tutorial
For this tutorial you will additionally need the files
- 105Indian_2527458snps.bed, .bim, .fam
- 108Malay_2527458snps.bed, .bim, .fam
- 110Chinese_2527458snps.bed, .bim, .fam
stored in the folders 'Lipidomic' and 'Genomics' contained in the following compressed file: https://sphfiles.nus.edu.sg/phg/Iomics/downloads/iOmics_data.tar.gz
UPDATE 25/06/2019: uncompressed
iOmics_data.tar.gz now directly available as
I noticed the URL recently changed. To avoid problems with tracking the data, I have now hosted all of them in this repo. It is no longer necessary to download from the link above.
- Combine the folders 'Lipidomic' and 'Genomics' and all files from this repo in your working directory.
- Install all packages listed on top of the scripts.
SNPRelateare deposited in BioConductor, all other packages in CRAN.
UPDATE 25/06/2019: Linux/macOS installation of GenABEL:
install.packages("GenABEL.data", repos="http://R-Forge.R-project.org") packageurl <- "https://cran.r-project.org/src/contrib/Archive/GenABEL/GenABEL_1.8-0.tar.gz" install.packages(packageurl, repos=NULL)
- Run the scripts in their exact numbered order.
This work was largely based on the following publications:
- Establishing multiple omics baselines for three Southeast Asian populations in the Singapore Integrative Omics Study, Saw et al. (2017), Nat. Comm. (data source)
- A guide to genome-wide association analysis and post-analytic interrogation, Reed et al. (2015), Stats. in Med. (method source)
Also, thanks to @nizzle10 and @rafalcode for contributing. Enjoy, all feedback is welcome!