June 13-14, 2019
9:00 am - 4:30 pm
Instructors: Sue McClatchy, Dan Gatti
Helpers: John Shorter
Where: 18 MacNider Hall, 333 South Columbia Street, University of North Carolina, Chapel Hill. Get directions with OpenStreetMap or Google Maps.
When: June 13-14, 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.). They should have a few specific software packages installed (listed below).
Code of Conduct: Everyone who participates is required to conform to the Code of Conduct.
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.
| 09:00 | Introductions and Workshop Overview |
| 09:30 | Input File Format |
| 10:00 | Calculating Genotype Probabilities |
| 10:45 | Coffee |
| 11:00 | Special covariates for the X chromosome |
| 11:30 | Performing a genome scan |
| 12:00 | Lunch break |
| 13:00 | Performing a genome scan (continued) |
| 13:30 | Performing a permutation test |
| 14:00 | Finding LOD peaks |
| 14:30 | Coffee |
| 14:45 | Calculating A Kinship Matrix |
| 15:45 | Performing a genome scan with a linear mixed model |
| 16:25 | Wrap-up |
| 16:30 | End |
| 09:00 | Performing a genome scan with a linear mixed model (brief review) |
| 09:30 | Performing a genome scan with binary traits |
| 09:45 | Estimated QTL effects |
| 10:45 | Coffee |
| 11:00 | Diversity Outbred Mice (lecture) |
| 12:00 | Lunch break |
| 13:00 | QTL analysis in Diversity Outbred Mice |
| 14:30 | Coffee |
| 14:45 | QTL analysis in Diversity Outbred Mice (continued) |
| 16:25 | Wrap-up |
| 16:30 | End |
We will use this collaborative document for chatting, taking notes, and sharing URLs and bits of code.
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.
R is a programming language that is especially powerful for data exploration, visualization, and statistical analysis. To interact with R, we use RStudio.
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.
Install R by downloading and running this .pkg file from CRAN. Also, please install the RStudio IDE.
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.
library(devtools)
install_github("rqtl/qtl2")
Make a new folder in your Desktop called mapping. Move into this new folder.
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.
setwd("~/Desktop")
dir.create("./mapping")
setwd("~/Desktop/mapping")
dir.create("./data")
dir.create("./scripts")
dir.create("./results")
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.
setwd("~/Desktop/mapping")
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.