ADPenetrance: Penetrance calculation for autosomal dominant traits

Updated 16/12/2022

The repository is maintained by Thomas Spargo (thomas.spargo@kcl.ac.uk) - please reach out with any questions.

This README outlines: * The contents of this repository * Links to documentation for the main R functions contained within

The approach followed here is described in full within the following publication (1) and is also available within a web app. ADPenetrance was developed on the basis of the disease model outlined here (2).

Repository contents

adpenetrance_function.R * Running this R script generates the function for this penetrance calculation approach, adpenetrance. * Use of adpenetrance requires the subfunctions adpenetrance.errorfit and adpenetrance.unadjusted to be loaded - these are retrieved from GitHub when running the adpenetrance_function.R script. * adpenetrance can be applied in accordance with this documentation.

getResidualRisk.R * Running this R script generates the getResidualRisk function. * This is a simple function to facilitate calculation of the disease model parameter g, which can be passed to the useG argument of adpenetrance as an indication of disease risk for family members not harbouring the tested variant.

checkOnsetVariability.R * Running this R script generates the checkOnsetVariability function. * This function centres and overlays the age of onset distributions (as a density or cumulative density function) across two groups. It can be used to test whether there is similar variability in disease onset for people with and without a variant, which is an indication that penetrance estimates in age-dependent traits may be less affected by age of sampling.

simADPenetrance.R * Running this R script generates the simADPenetrance function. * simADPenetrance can be used to easily perform simulation studies to test possible effects of age of sampling upon penetrance estimation when there is unequal onset variability between groups (as indicated by the output of checkOnsetVariability). * This function is dependent upon the main adpenetrance function and subfunctions, and subfunctions within the subfunctions/ directory - each of these dependencies are automatically retrieved from GitHub when running simADPenetrance.R. * It is also dependent upon the R packages ggplot2, plyr, reshape2, which must be installed and loaded by the user.

approach_validation/

This directory contains scripts utilised as part of validation for this approach to penetrance calculation.

Please refer to the README documentation within the approach_validation/ directory which describes the contents and validation steps taken.

case_studies/

       case_data.csv * This contains the raw sample data for all case studies described in the publication associated with this repository (1).

       publishedcasestudies.R * This script calls the adpenetrance and getResidualRisk functions and case_data.csv to estimate penetrance for case studies represented within case_data.csv.

subfunctions/

This directory contains several functions which are utilised internally when running adpenetrance or simADPenetrance.

Details regarding each function are providied within, and in the repository wiki.

References

1. Spargo, T. P., Opie-Martin, S., Bowles, H., Lewis, C. M., Iacoangeli, A., & Al-Chalabi, A. (2022). Calculating variant penetrance from family history of disease and average family size in population-scale data. Genome Medicine 14, 141. doi: 10.1186/s13073-022-01142-7

2. Al-Chalabi, A. & Lewis, C. M. (2011). Modelling the Effects of Penetrance and Family Size on Rates of Sporadic and Familial Disease. Human Heredity, 71(4): 281-288. doi: 10.1159/000330167