Chris Wallace's Projects
code to generate figures for abasis manuscript
Using Approximate Bayesian Computation to fine map causal variants from GWAS summary data.
📝 Easily create a beautiful website using Academic, Hugo, and Netlify
permutation to adjust optiomistic p values
Allan Lab website
repo for R package annotSnpStats
Autoimmunity in Pulmonary Arterial Hypertension
cluster beta/gaussian mixture data
faster cFDR using Rcpp, but not adaptation for common controls
Implements conditional false-discovery rate hypothesis testing, used to perform high-dimensional hypothesis tests. Requires a set of summary statistics in an experiment of interest, and 'levers' on a second set of summary statistics at the same variables for a second experiment. Enables frequentist hypothesis testing with overall strong control of false-discovery rate. Can use several estimators of the cFDR function.
This repository contains R functions to compute the 'Conditional False Discovery Rate', a method to analyse genome-wide association studies (GWAS) for related diseases originally proposed by Andreasson et al (2013), in the case where the two GWAS have shared controls.These functions widen the scope of the existing technique and enable improved power.
Capture Hi-C gene prioritiser
README on main github page
Group website
Power calcs for cluster
Repo for the R package coloc
R code used to explore appropriate p value thresholds for calling genetic association in one disease given genomewide significant genetic association at the same SNP in a related disease in the T1D ImmunoChip paper (Onengut et al, in press)
Repo for corrcoverage package
R Package for PCA analysis of Genome Wide Association Studies (GWAS)
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent