mvab / mr_sleep_traits_breast_cancer

Sleep traits / BMI / breast cancer MR project

Background

to add

This repository

Main analysis scripts and metadata (see details below):

├── set_paths.R
├── 01_process_gwas_summary.Rmd
├── 02_mr_BMI_to_mediators.Rmd
├── 03_mr_mediators_to_BC.Rmd
├── 04_mvmr_run_analysis.Rmd
├── 05_mvmr_create_plots.Rmd * not added yet
├── 06_mediation_analysis.Rmd  
├── functions.R
├── functions_mvmr.R
├── metadata
│   └── data_lookup.csv
│   └── pheno_correlations.csv

How to reproduce this analysis, i.e. Main Workflow

1. Script set_paths.R is imported by all other scripts, and is used to set the environment of where the project is run.

2. Rmd 01_process_gwas_summary.Rmd is required for processing data that comes as text files (i.e. GWAS summary stats) from the IEU GWAS pipeline or other sources. This script has to be run to convert raw data into outcome data frames and to extract instruments from each GWAS (in exposure format) and save them to be used directly in MR analysis in subsequent scripts. The names of raw files, tidy outcome data frames, and exposure instruments are all get saved in the metadata file data_lookup.csv upon generation. (NB the metadata file has to contain raw file names and the desired output prefixes before running this Rmd).

3. Rmd 02_mr_BMI_to_mediators.Rmd runs univariable MR of Childhood and Adult BMI on all mediators specified in metadata file (data_lookup.csv). The code has to be run interactively per trait category. The results merged by trait category will be stored in Results directory outside the codebase. After the analysis, forest plots can be created for each trait category. To recreate the plots, don't need to rerun the full analysis, can just read in the merged files. The plots will be saved in the codebase in figures/.

4. Rmd 03_mr_mediators-to-BC.Rmd is used to run univariable MR of all mediators (and BMI) on Breast cancer (ieu-a-1126). The code has to be run interactively per trait category, the results are stored in Results outside the codebase. After the analysis, forest plots can be created for each trait category. To recreate the plots, don't need to rerun the full analysis, can just read in the merged files. The plots will be saved in the codebase in figures/.

5. Rmd 04_mvmr_run_analysis.Rmd runs four types of MVMR with each mediator, but first we run MVMR with BMIs only (Analysis 0).

   • (Analysis 0) multivariable MR: childhood BMI + adult BMI -> Breast Cancer
   • (Analysis 1) multivariable MR: childhood BMI + adult BMI -> mediator
   • (Analysis 2) multivariable MR: childhood BMI + mediator -> Breast Cancer
   • (Analysis 3) multivariable MR: adult BMI + mediator -> Breast Cancer
   • (Analysis 4) multivariable MR: childhood BMI + adult BMI + mediator -> Breast Cancer

   The code has to be run interactively per trait category, the results are stored in Results/trair_category/ outside the codebase. The analysis is structured as a large for-loop that will perform all four MVMR for each mediator in the selected trait category when individually specified T/F outside the loop. After all analyses have been performed, the mediators within each trait category are collated into a single dataframe and saved in Results/trait_category/merged/ directory.

MVMR analysis is performed using modified code from TwoSampleMR package and also MVMR package for comparison. MVMR sensitivity tests are done using MVMR package and phenotypic correlations estimated using metaCCA package.

6. Rmd 05_mvmr_create_plots.Rmd creates forest plots from all MVMR analyses for each trait category separately and by trait category. The plots are saved to figures within the codebase. The code also creates summary plot of all direct Childhood BMI estimates from Analyses 2 & 3.

7. Rmd 06_mediation_analysis.Rmd contains a workflow for performing MR mediation analysis using Difference and Product method, with CIs calculation using Delta and Propagation of Errors methods. The script also contains methods for plotting the calculated indirect estimates (+CIs) as forest plots.