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README.Rmd
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---
title: "Practical MR session using R"
output: github_document
bibliography: bib/readme.bib
nocite: |
@davey_smith_mendelian_2003, @davey_smith_mendelian_2014, @hartwig_two-sample_2016, @bowden_mendelian_2015, @davies_reading_2018, @burgess_guidelines_2019, @slob_comparison_2020, @noauthor_mendelian_nodate, @burgess_review_2017
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(
echo = TRUE,
collapse = TRUE,
comment = "#>"
)
```
This repository contains material of the Mendelian Randomization (MR)
session within the [Online Summer School 2021: Genetic Epidemiology of Kidney Function and Chronic Kidney Disease](https://geneticepisummerschool.eurac.edu/).
The session will cover practical aspects regarding the implementation
of Mendelian Randomization (MR) analyses. The course is focused on
two-sample MR applications using summary-level data from genome-wide
association studies (GWAS). References on methodology and software
for one-sample MR methods will be also provided.
To download all the session material, click on `Code -> Download ZIP`.
Then save the _.zip_ file locally and extract all the material of the
course.
The main folders are organized as follows:
* **data** folder contains the raw GWAS summary-level data that
are used in the case study. The files are in *.txt* format.
* **scripts** folder contains the R script that is used for the case
study during the session
* **slides** folder contains all the files that are used to create the
slides for the presentation
* **vignettes** folder contains all the files that are used to create
the tutorial document.
The tutorial document contains a summary of the case study used to show
MR analysis workflow. It can be found [here](vignettes/tutorial.md).
A PDF version of the presentation can be found [here](slides/session_slides.pdf). Please use Google Chrome browser for
a correct visualization of the PDF file.
All the other folders and files should not be moved or deleted for
reproducing the material of the session.
**Note**: the material will be continuously updated until the day of
the session, i.e. July 14th, 2021. After the session, updates will be
performed based on requests or suggestions from the users. If you need
to make a request, please open an issue [here](https://github.com/EuracBiomedicalResearch/trainckdis.mr/issues).
## Program
1. __Data preparation__:
+ Collecting summary-level genome-wide association studies (GWAS)
data from online repositories
+ Data harmonization with `TwosampleMR` R package
2. __Running MR analysis__:
+ Estimating causal effects using `MendelianRandomization` and
`TwoSampleMR` R packages
+ Displaying and interpreting results
3. __Sensitivity analyses__:
+ Evaluating if MR assumptions are supported by the data
+ Estimating causal effects with robust MR methods
## Prerequisites
The session will be taught in `R` (see [here](https://www.r-project.org/)
for more information). Previous knowledge of `R` programming can be
helpful although not mandatory.
## Software setup
* Please download and install the latest `R` version from [here](https://www.r-project.org/)
* For Windows users, please download and install the `Rtools` version
compatible with the latest `R` version installed on your machine
from [here](https://cran.r-project.org/bin/windows/Rtools/history.html).
Please use the [following tutorial](https://cran.r-project.org/bin/windows/Rtools/)
(see _Putting Rtools on the PATH_) to properly set up `Rtools`.
* Although it is not mandatory, it is recommended to download and
install the latest `RStudio` version from [here](https://www.rstudio.com/products/rstudio/download/) (free version)
since `RStudio` will be used during the session
* Please download and install the latest version of the following
`R` packages from CRAN:
```r
install.packages(
c(
"remotes",
"devtools",
"MendelianRandomization",
"ggplot2"
),
dependencies = TRUE
)
```
* Please download and install the latest version of `TwoSampleMR` from
Github repository:
```r
remotes::install_github("MRCIEU/TwoSampleMR")
```
## Software introduction
Introductory material on `R`, `Rstudio` and `R` packages to implement
one-sample and two-sample MR is provided below. We suggest the students
to check the material before the beginning of the session to start
practicing with `R` programming and the packages that will be used
throughout the session
### Setting-up R
* See [Chapter 1 of ModernDive](https://moderndive.netlify.app/1-getting-started.html) for beginner-friendly guide to install `R` and `Rstudio`
* See [BasicBasics 1 and 2](https://rladiessydney.org/courses/ryouwithme/01-basicbasics-0/) for
a gentle introduction to basic commands in `R`
### Two-sample MR packages
* [Introduction to the `TwoSampleMR` package](https://mrcieu.github.io/TwoSampleMR/articles/index.html)
* [Introduction to the `MendelianRandomization` package](https://mrcieu.github.io/TwoSampleMR/articles/index.html)
### One-sample MR packages
* `ivreg` function in [`AER` R package](https://cran.r-project.org/web/packages/AER/index.html) or
`tsls` function in [`sem` R package](https://cran.r-project.org/web/packages/sem/index.html) to implement two-stage least squares (2SLS) method
* [`ivtools` R package](https://cran.r-project.org/web/packages/ivtools/index.html) to implement several one-sample MR methods
## Contributions
| Name | Affiliation |
|:----------------------------------------------------------------------|:-------------------------------------------------------------------------------------------------------------------|
| [Daniele Bottigliengo](https://github.com/danielebottigliengo) | [EURAC Research, Institute for Biomedicine](https://www.eurac.edu/en/institutes-centers/institute-for-biomedicine) |
| [Adrienne Tin](https://scholar.google.com/citations?user=8FfPK3gAAAAJ&hl=en) | [University of Mississippi Medical Center](https://www.umc.edu/) |
| [Alexander Teumer](https://loop.frontiersin.org/people/339263/overview) | [Institute for Community Medicine, University Medicine Greifswald](https://www2.medizin.uni-greifswald.de/icm/index.php?id=19&L=1) |
## Reading list
Before starting the session, the reading of the following papers is
suggested: