Genome-wide Association Identifies Novel Etiological Insights Associated with Parkinson’s Disease in African and African Admixed Populations
GP2 ❤️ Open Science 😍
Last Updated: April 2023
This is the online repository for the manuscript titled "Genome-wide Association Identifies Novel Etiological Insights Associated with Parkinson’s Disease in African and African Admixed Populations". This study represents the first and largest genome-wide assessment of Parkinson’s disease in the African and African admixed populations.
All data was using release 5 GP2 data (access-controlled via single-sign on on amp-pd.org) and 23andMe GWAS summary statistics (available via collaboration with 23andMe).
- The
analyses/
directory includes all analyses discussed in the manuscript - The
figures/
directory includes all figures and supplemental figures referenced in the manuscript (pending publication) - The
tables/
directory includes all tables and supplemental tables referenced in the mansucript (pending publication)
- Languages: Python, bash, and R
Notebooks | Description |
---|---|
00_Prepping_Data | Cleaning data and generating covariate files |
01_perGroup_GWASes | Running GWASes per group (no indels, age, sex, PCs 1-10 as covariates) |
02_formatMETAL | Format additive summary statistics for meta-GWASes with METAL |
03_AAC_ONLY_META | Meta-GWAS #1: Looking at African admixed individuals only |
04_AFR_ONLY_META | Meta-GWAS #2: Looking at African individuals only |
05_AFR_AAC_Combined_META | Meta-GWAS #3: Looking at African and African admixed individuals |
06_Investigate_Hits | Investigating the top hits from the joint meta-GWAS |
07_BetaBeta_Plots | Generating beta-beta plots |
08_Zygosity_rs3115534 | Get the zygosity distribution of individuals for rs3115534 |
09_Manhattan_QQ_Plots | Visualize the meta-GWASes |
10_Compare_GWASes_NallsFooKim | Seeing the number of variants from the previously identified 104 that show up in our meta-GWAS |
11_PRS_Nalls2019_90_EUR-GLM | Conducting PRS on cohorts: Pulling the 90 European variants from Nalls et al., 2019 and using European betas |
12_PRS_23andMe_90_EUR-GLM | Conducting PRS on cohorts: Pulling the 90 European variants from Nalls et al., 2019 and using AAC betas from 23andMe summary statistics |
13_adHoc_Analyses | Runs of homozygosity, linear regression for % admixture and age, haplotypes with 1KG, fine-mapping, dominant vs recessive modeling, annotating WGS for T2, conditional analysis, Miami plot compared to Europeans, and GBA Gauchian caller WDL |
(pending publication)
(pending publication)
Software | Version(s) | Resource URL | RRID | Notes |
---|---|---|---|---|
ANNOVAR | 2020-06-08 | http://www.openbioinformatics.org/annovar/ | RRID:SCR_012821 | refGene; avsnp150; ljb26_all; gnomad312_genome; used for annotation |
coloc | 5.1.0.1 | https://cran.r-project.org/web/packages/coloc/index.html | N/A | R package; used for fine-mapping |
GBA Gauchian caller | 1.0.2 | https://github.com/Illumina/Gauchian | N/A | Illumina's targeted variant caller for the GBA gene based on a whole-genome sequencing (WGS) |
METAL | 2020-05-05 | http://csg.sph.umich.edu//abecasis/Metal/ | RRID:SCR_002013 | used for meta-analyses |
PLINK | 1.7 and 1.9 and 2.0 | http://www.nitrc.org/projects/plink | RRID:SCR_001757 | used for genetic analyses |
Python Programming Language | 3.8 and 3.9 | http://www.python.org/ | RRID:SCR_008394 | pandas; numpy; seaborn; matplotlib; statsmodel; used for general data wrangling/plotting/analyses |
R Project for Statistical Computing | 4.2 | http://www.r-project.org/ | RRID:SCR_001905 | tidyverse; dplyr; tidyr; ggplot; data.table; used for general data wrangling/plotting/analyses |