- If you do not want to install every software needed for the Polyploid Training Workshop
- If you want to run every software via RStudio in your web browser
- If you want to use a cluster to run the analysis
All images will run on top of your OS kernel, so they are cross-platform enabled, do not need any configuration, and are ready to go.
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Images to run self-contained containers with the following software:
Linux users: use the following instructions to Install Docker on Ubuntu, or find your distribution here.
Mac users: download the Docker Desktop Installer for Mac and follow the Installation instructions for Mac.
Windows users: first, install and configure Windows Subsystem for Linux (steps 1-5 only). Then, download the Docker Desktop Installer for Windows and run it. Once the installation finishes, you will be able to open a Windows Powershell terminal and run the commands under the Running instructions sessions below. If you have any problem, please follow the Installation instructions for Windows or ask for help on our Slack Channel.
Cluster users: most computing clusters already have Docker or Singularity installed - you can jump to the next session, download, and run the images. If your cluster does not have any image rendering system, please contact your system administrator. This information may help you to elaborate a request.
Docker requires administrator permissions to run. If you do not have these permissions, you can use Singularity. Here are some instructions about how to use Docker images with Singularity.
After installing docker here are some useful commands:
# Dowload images and run containers
docker pull # Get image from a registry
docker run # run a command in a new container
docker run -it -v # run in an interactive mode and transferring directory to the container environment
# Delete container
docker ps # list all containers available on your computer, search the container you want to delete
docker stop <cointainer_id> # before delete you should stop it
docker rm <cointainer_id> # delete container using the same ID
# Delete image
docker images # list all images available on your computer, search the image ID that you want to delete
docker rmi <image_id> # delete the image using the same ID
# Delete all images and containers
docker stop $(docker ps -a -q) # stop all running containers
docker rm $(docker ps -a -q) # remove all stopped containers
docker rmi $(docker images -q) # remove all images
- Docker Hub image: cristaniguti/poly_genocalls
Image contents
- Ubuntu 20.04
- R 4.0.3
- RStudio 1.3
- Python 2.7
- SuperMASSA
- VCF2SM
- polyRAD
- fitPoly
Running instructions
Download the container image: open a terminal and run: docker pull cristaniguti/poly_genocalls
Then start the image by running the following commands (feel free to choose another port different than 8787):
# Running VCF2SM (Linux/Mac)
docker run -v $(pwd):/home/user/ cristaniguti/poly_genocalls python /scripts/VCF2SM.py -i /opt/subset.vcf -o /home/user/example_poly.vcf -S /scripts/SuperMASSA.py -I hw -a RA/AA -r 1:84 -d 15 -D 500 -M 4:6 -f 4 -p 0.80 -n 0.90 -c 0.75 -t 1
# Running VCF2SM (Windows)
docker run -v ${pwd}:/home/user/ cristaniguti/poly_genocalls python /scripts/VCF2SM.py -i /opt/subset.vcf -o /home/user/example_poly.vcf -S /scripts/SuperMASSA.py -I hw -a RA/AA -r 1:84 -d 15 -D 500 -M 4:6 -f 4 -p 0.80 -n 0.90 -c 0.75 -t 1
# Access the RStudio (Linux/Mac)
docker run -p 8787:8787 -v $(pwd):/home/rstudio/ -e DISABLE_AUTH=true cristaniguti/poly_genocalls
# Access the RStudio (Windows)
docker run -p 8787:8787 -v ${pwd}:/home/rstudio/ -e DISABLE_AUTH=true cristaniguti/poly_genocalls
Keep this terminal open and access http://localhost:8787/ or http://127.0.0.1:8787/ in your web browser. You can also run the VCF2SM using the RStudio terminal, but do not forget the path of the scripts inside the container: /scripts/SuperMASSA.py and /scripts/VCF2SM.py. If you want to load files or folders into the container, simply run the commands above from a directory containing them (you can use commands such as cd and cd .. to navigate through directories).
Attention: If running on Windows PowerShell probably your default path is C:\WINDOWS\system32 and your output files can be written on it. For example, running the VCF2SM command shown above, the output example_poly.vcf will be found at that path. If you want to change the directory, please use cd, as shown before. Here we show a simple example:
- Change the directory to the Documents folder of your user:
cd C:\Users\YOURUSER\Documents - Create a directory for the first day of the Polyploid Training Workshop:
mkdir PTWD1 - Access the folder:
cd .\PTWD1 - If you run the docker command for
VCF2SM, you will find the output within this folder.
Warning: container images can be large depending on their content. If you do not plan to use the images soon and want to free up some storage space, please see Docker useful commands session to remove them.
- Docker Hub image: cristaniguti/poly_haplo
Image contents
- Ubuntu 20.04
- R 4.0.3
- RStudio 1.3
- Julia 1.5.3
- MAPpoly
- polymapR
- PolyOrigin
Running instructions
Download the container image: open a terminal and run: docker pull cristaniguti/poly_haplo
Then start the image by running the following commands (feel free to choose another port different than 8787):
# Running Julia (Linux/Mac)
docker run -it -v $(pwd):/opt cristaniguti/poly_haplo /scripts/./julia
# Running Julia (Windows)
docker run -it -v ${pwd}:/opt cristaniguti/poly_haplo /scripts/./julia
# Access the RStudio (Linux/Mac)
docker run -p 8787:8787 -v $(pwd):/home/rstudio/ -e DISABLE_AUTH=true cristaniguti/poly_haplo
# Access the RStudio (Windows)
docker run -p 8787:8787 -v ${pwd}:/home/rstudio/ -e DISABLE_AUTH=true cristaniguti/poly_haplo
Keep this terminal open and access http://localhost:8787/ or http://127.0.0.1:8787/ in your web browser. You can also run the Julia using the RStudio terminal, but do not forget the path of the script inside the container: /scripts/julia. If you want to load files or folders into the container, simply run the commands above from a directory containing them (you can use commands such as cd and cd .. to navigate through directories).
With RStudio, try to load any of the included R packages:
# Loading MAPpoly
library(mappoly)
plot(solcap.err.map[[1]])
If you see the same plot shown above, you are ready to go! We recommend that you start by following the vignettes and examples for each package.
Warning: container images can be large depending on their content. If you do not plan to use the images soon and want to free up some storage space, please see Docker useful commands session to remove them.
- Docker Hub image: cristaniguti/poly_qtl
Image contents
- Ubuntu 20.04
- R 4.0.3
- RStudio 1.3
- QTLpoly
- diaQTL
- GWASpoly
Running instructions
Download the container image: open a terminal and run: docker pull cristaniguti/poly_qtl
Then start the image by running the following commands (feel free to choose another port different than 8787):
# Access the RStudio (Linux/Mac)
docker run -p 8787:8787 -v $(pwd):/home/rstudio/ -e DISABLE_AUTH=true cristaniguti/poly_qtl
# Access the RStudio (Windows)
docker run -p 8787:8787 -v ${pwd}:/home/rstudio/ -e DISABLE_AUTH=true cristaniguti/poly_qtl
Keep this terminal open and access http://localhost:8787/ or http://127.0.0.1:8787/ in your web browser. If you want to load files or folders into the container, simply run the commands above from a directory containing them (you can use commands such as cd and cd .. to navigate through directories).
Inside RStudio, try to load any of the included packages:
# Loading QTLpoly
library(qtlpoly)
load(pheno)
head(pheno)
## T32 T17 T45
## Ind_1 -0.1698446 -0.9332320 -1.2259338
## Ind_2 2.5319356 0.1997378 -1.8004184
## Ind_3 1.3669074 1.0584794 -0.7980037
## Ind_4 0.7955652 -1.7186921 1.5834176
## Ind_5 1.3168502 -0.7119421 1.3099067
## Ind_6 -0.8778211 -0.2339543 -0.6323779
If you see the output shown above, you are ready to go! We recommend that you start by following the vignettes and examples for each package.
Warning: container images can be large depending on their content. If you do not plan to use the images soon and want to free up some storage space, please see Docker useful commands session to remove them.
If you find any problem or want to add more software to the images, or even create a new one, feel free to send us messages, open issues, or pull requests.