Polygenic gene editing: the next frontier in genomic medicine?

Data and R scripts to generate Figures - Perspective paper on Gene Editing - Visscher et al. (2023) This folder contains GWAS summary statistics (genome-wide significant SNPs only) for various traits and diseases, as well as R scripts to generate Figures from our Perspective paper on Gene Editing. Data Files FG_36snps.txt: Fasting Glucose - data from Lagou et al. (2021) WHRadjBMI_Pullit_et_al2018.txt: Waist-Hip Ratio adjusted for BMI - data from Pullit et al. (2018) GLGC_Graham2021.txt: Summary statistics for LDL, (log) Triglycerides - data from Graham et al. (2021) ICBP_Warren2022.txt: Summary statistics for blood pressure phenotypes (systolic and diastolic) - data from Warren et al. (2022) ad_marioni2018_ukbf.txt: Summary statistics for Alzheimer's Disease - data from Marioni et al. (2018) mdd_howard2019_ukbf.txt: Summary statistics for Major Depression Disorder - data from Howard et al. (2019) scz_ng2014_ukbf.txt: Summary statistics for Schizophrenia - PGC consortium (2014) t2d_Vujkovic2020.txt: Summary statistics for type 2 diabetes - ref. https://www.nature.com/articles/s41588-020-0637-y#Sec45 cad_aragam2021.txt: Summary statistics for Coronary Artery Disease - ref. https://www.medrxiv.org/content/10.1101/2021.05.24.21257377v1.full.pdf summary_stats_GWS_Yengo_Savage_2018_v2.Rdata: Summary statistics for height and BMI (Yengo et al. (2018)) and IQ (Savage et al. (2019)). R Script Files Figure_1.R Figure_2.