jamesliley's repositories
cfdr
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.
cFDR-common-controls
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.
cfdr_control_pipeline
Pipeline for generation of all plots and results in paper 'Accurate error control in high dimensional association testing using conditional false discovery rates' by James Liley and Chris Wallace (to be submitted)
cfdr_estimation_pipeline
Pipeline for generation of all plots and results in paper 'New estimators for conditional false discovery rates improve power and smoothness' by James Liley and Chris Wallace (to be submitted)
cfdr_pipeline
Pipeline to generate all results in manuscript 'Accurate error control in high dimensional association testing using conditional false discovery rates', by James Liley and Chris Wallace
example_repo
An example repository containing simple code
model_updating
Supporting code for manuscript 'Model updating after interventions paradoxically introduces bias'
OptHoldoutSize
R package for estimation of optimal size of a 'holdout' set for planned updating of a predictive score
OptHoldoutSize_pipelines
Pipelines to generate figures and data used in Optimal Holdout Sizing manuscript
SPARRAfairness
Code and data for SPARRAfairness R package on CRAN
Stacked_interventions
Code to support manuscript. Contains simulations