Quantitative Trait Mapping in the Diversity Outbred

Aug 22-23, 2019

9:00 am - 4:30 pm

Instructors: Dan Gatti, Sue McClatchy

Helpers: Anne Deslattes Mays

General Information

Where: Bioinformatics Training Room, 600 Main Street, Bar Harbor ME. Get directions with OpenStreetMap or Google Maps.

When: Aug 22-23, 2019. Add to your Google Calendar.

Requirements: Participants must bring a laptop with a Mac, Linux, or Windows operating system (not a tablet, Chromebook, etc.) that they have administrative privileges on. They should have a few specific software packages installed (listed below).

Code of Conduct: Everyone who participates in Carpentries activities is required to conform to the Code of Conduct. This document also outlines how to report an incident if needed.

Accessibility: We are committed to making this workshop accessible to everybody. The workshop organizers have checked that:

Materials will be provided in advance of the workshop and large-print handouts are available if needed by notifying the organizers in advance. If we can help making learning easier for you (e.g. sign-language interpreters, lactation facilities) please get in touch (using contact details below) and we will attempt to provide them.

Contact: Please email susan.mcclatchy@jax.org for more information.


Please be sure to complete these surveys before and after the workshop.

Pre-workshop Survey

Post-workshop Survey


We will use this collaborative document for chatting, taking notes, and sharing URLs and bits of code.


QTL mapping with qtl2


To participate in a workshop, you will need access to the software described below. In addition, you will need an up-to-date web browser.

We maintain a list of common issues that occur during installation as a reference for instructors that may be useful on the Configuration Problems and Solutions wiki page.


R is a programming language that is especially powerful for data exploration, visualization, and statistical analysis. To interact with R, we use RStudio.

Video Tutorial

Install R by downloading and running this .exe file from CRAN. Also, please install the RStudio IDE. Note that if you have separate user and admin accounts, you should run the installers as administrator (right-click on .exe file and select "Run as administrator" instead of double-clicking). Otherwise problems may occur later, for example when installing R packages.

You can download the binary files for your distribution from CRAN. Or you can use your package manager (e.g. for Debian/Ubuntu run sudo apt-get install r-base and for Fedora run sudo dnf install R). Also, please install the RStudio IDE.


The qtl2 package contains code for haplotype reconstruction, QTL mapping and plotting.

Option 1: R/qtl2 is not yet available on CRAN, but it can be installed from a mini-CRAN at rqtl.org. Make sure you have the latest version of R (3.4.4).

Option 2: Alternatively, you can install R/qtl2 from its source on GitHub. (But note that compiling the C++ code can be rather slow.)

On Windows, you’ll need Rtools.

On Mac OS X, you’ll need the command-line developer tools, as well as gfortran.

You then need to install the devtools package, plus a set of package dependencies: yaml, jsonlite, data.table, and RcppEigen. (Additional, secondary dependencies will also be installed.) Start RStudio, then copy and paste the following code into the R console in RStudio.

install.packages(c("devtools", "yaml", "jsonlite", "data.table", "RcppEigen", "RSQLite", "qtl"))

Finally, install R/qtl2 using devtools::install_github(). Copy and paste the following code into the R console in RStudio.


Data files and project organization

  1. Make a new folder in your Desktop called mapping. Move into this new folder.

  2. Create a data folder to hold the data, a scripts folder to house your scripts, and a results folder to hold results.

Alternatively, you can use the R console to run the following commands for steps 1 and 2.

  1. Please download the following large files before the workshop, and place them in your data folder. You can download the files from the URLs below and move the files the same way that you would for downloading and moving any other kind of data.

Alternatively, you can copy and paste the following into the R console to download the data.

download.file("https://ndownloader.figshare.com/files/9746485", "./data/cc_variants.sqlite")
download.file("https://ndownloader.figshare.com/files/9746458", "./data/mouse_genes.sqlite")
download.file("https://ndownloader.figshare.com/files/9746452", "./data/mouse_genes_mgi.sqlite")
download.file("ftp://ftp.jax.org/dgatti/qtl2_workshop/qtl2_demo.Rdata", "./data/qtl2_demo.Rdata")

You will need these for the final lesson episodes on SNP association mapping and QTL analysis in Diversity Outbred mice.