GenSpace 2020 Workshop on Personalized Medicine using Pharmacogenomics (July 26, 2020)

Calculating Polygenic Risk Scores

Materials in this git repository contains materials used during the GenSpace 2020 Workshop on Personalized Medicine.

Materials found here are thanks to the inspiration from Laramie Duncan, PhD and Hanyang Shen from Stanford University and Sam Choi, PhD from Icahn School of Medicine, Mount Sinai

The materials in this repo include:

1. GenSpace-Pgx_day2.pdf : Lecture notes used for the workshop. Sources of materials are cited in the slide deck and pulled together by Kumar Veerapen and Caitlin Cooney.

2. Dockerfile : The hands on section of the workshop was run using the Hail team container service. The Dockerfile was used to create a docker image that was used for each container notebook deployment. It also installs the R Jupyter notebook functio and R:fmsb. The docker image used for the workshop was gcr.io/hail-vdc/genspace_pgx:0.4

3. resources directory: contains files needed for the running of this workshop materials where

   • GenSpace-Pgx_day2.ipynb is the R Jupyter notebook that allows you to run the commands used in this workshop. If you thought that Jupyter notebook was only for Python think again! You can use R as well. How did I set this up? Look here
   • a copy of plinkv1.90 is included in this repository.
   • binary PLINK files Pherandom.reduced_1000_Genomes of .bim, .fam, .bed are listed as Pherandom.reduced_1000_Genomes. These files are referred to and elaborated in the R Jupyter notebook in this repository.
   • p-values and effect sizes (beta values) are listed as MDD_2019_ files. These files are referred to and elaborated in the R Jupyter notebook in this repository.
   • q.ranges.GWASsig_to_1: p-value tranche file. This file is referred to and elaborated in the R Jupyter notebook in this repository.
   • OUTCOME is a directory that contains the results, and where your results will write into if you are using the main notebook GenSpace-Pgx_day2.ipynb.

   Ancilliary notebooks

   • BestFitCheckingPlotting.ipynb : additional python notebook to check for best fitting p-value tranche. This notebook is very raw. The annotations are not perfect but you can use this after running the main R notebook (GenSpace-Pgx_day2.ipynb) to see which p-value tranche worked best.
   • QCstepsTaken.ipynb : What QC steps can you take to clean up your data before running PRS calculations. This notebook is very raw. The annotations are not perfect and was meant as a placeholder for future QC classes.
   • QC is a directory that contains QC results from the data if you are using an ancilliary notebook (QCstepsTaken.ipynb)

4. GenSpace-Pgx_day2_notebookOutput.pdf : This file contains the LaTeX exported pdf output.

Good luck with running your PRS!

If you have any questions, feel free to email me.

If you are using any materials from here, PLEASE cite this git repository https://github.com/mkveerapen/genspace_pgx2020.