This repository contains the notes and code for the multi-ethnic transcriptome-wide association study of prostate cancer. Preliminary results of this study were presented at the 69th Annual Meeting of the American Society of Human Genetics in Houston, TX. The final results were subsequently published in 2020 as :
Fiorica PN, Schubert R, Morris JD, Abdul Sami M, Wheeler HE (2020) Multi-ethnic transcriptome-wide association study of prostate cancer. PLoS ONE 15(9): e0236209. https://doi.org/10.1371/journal.pone.0236209
Initial genotypes and phenotypes were downloaded from the NCBI Database of Genotypes and Phenotypes (dbGaP): Accession number phs000306.v4.p1
Information in this folder was compiled by Peter Fiorica starting in the Summer of 2019. This folder contains markdown documents for the the quality control, imputation, and association studies of the genotype and transcriptome data. Notes and command line executions are included as they are completed.
This folder contains notes and scripts compiled by Peter Fiorica Starting in September 2019. These notes and scripts are used for our study of prostate cancer in a self-identified Japanese American population. The folder contains R markdown documents in their .rmd version and their knitted .html version. These notes provide an overview of quality control, imputation, and association studies of the genotype and transcriptome data.
This folder contains notes and scripts compiled by Peter Fiorica Starting in September 2019. These notes and scripts are used for our study of prostate cancer in a self-identified Latin American population. The folder contains R markdown documents in their .rmd version and their knitted .html version. These notes provide an overview of quality control, imputation, and association studies of the genotype and transcriptome data. Notes and command line executions are included as they are completed.
This folder contains notes to generate the figures as referenced in the publication of this data above.
Information in this folder was compiled by Jack Morris and Mohammed Abdul Sami from 2017 to Spring 2019. The notes for this information are organized as follows:
1-12 are PRE-SUMMER 2018
13+ is POST-SUMMER 2018
This folder contains the PrediXcan association results for all three study populations. Gene expression was imputed using prediction models from GTEx V8 and MESA. The association files are separated to reflect this. GWAS summary statistics for each population in this study can be found on the NCBI GWAS Catalog.
Any questions abouts the contents of this repository can be directed to Peter Fiorica at [email protected] .