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\n\n\n### Mounting Additional Volume\n\nOne such option for `docker run` is `-v` to mount an additional volume\nto the docker image. This might be useful for say mounting a local R\ninstall directory for use on the docker. The path on the docker image\nthat should be mapped to a local R library directory is\n`/usr/local/lib/R/host-site-library`.\n\nThe follow example would mount my locally installed packages to this\ndocker directory. In turn, that path is automatically loaded in the R\n`.libPaths` on the docker image and all of my locally installed\npackage would be available for use.\n\n* Running it interactively,\n\n\t\tdocker run \\\n\t\t\t-v /home/my-devel-library:/usr/local/lib/R/host-site-library \\\n\t\t\t-it \\\n\t\t\t--user rstudio \\\n\t\t\tbioconductor/bioconductor_docker:devel\n\n without the `--user rstudio` option, the container is started and\n logged in as the `root` user.\n\n The `-it` flag gives you an interactive tty (shell/terminal) to the\n docker container.\n\n* Running it with RStudio interface\n\n\t\tdocker run \\\n\t\t\t-v /home/my-devel-library:/usr/local/lib/R/host-site-library \\\n\t\t\t-e PASSWORD=password \\\n\t\t\t-p 8787:8787 \\\n\t\t\tbioconductor/bioconductor_docker:devel\n\n\n\n### Using docker-compose\n\nTo run the docker-compose file `docker-compose.yaml` from the same\ndirectory,\n\n```\ndocker-compose up\n```\n\nUsing `docker-compose`, the user can launch the image with a single\ncommand. The RStudio image is launched at `http://localhost:8787`.\n\nThe `docker-composer.yaml` includes settings so that the user doesn't\nhave to worry about setting the port, password (default is `bioc`), or\nthe volume to save libraries.\n\nThe library path, where all the packages are installed are\nautomatically configured to use the volume\n`$HOME/R/bioconductor_docker/`, in the case of\nthe Bioconductor version 3.14, it would be\n`$HOME/R/bioconductor_docker/3.14`. This location is mounted on to the\npath, `/usr/local/lib/R/host-site-library`, which is the first value\nin your search path for packages if you check `.libPaths()`.\n\nWhen the user starts the docker image using `docker-compose`, it will\nrecognize previously mounted libraries with the apprpriate\nbioconductor version, and save users time reinstalling the previously\ninstalled packages.\n\nTo add another volume for data, it's possible to modify the\n`docker-compose.yml` to include another volume, so all the data is\nstored in the same location as well.\n\n```\nvolumes:\n\t- ${HOME}/R/bioconductor_docker/3.14:/usr/local/lib/R/host-site-library\n\t- ${HOME}/R/data:/home/rstudio\n```\n\n\nTo run in the background, use the `-d` or `--detach` flag,\n\n```\ndocker-compose up -d\n```\n\nIf the image is run in a detached state, the `container-name` can be\nused to exec into the terminal if the user wishes `root` access in a\nterminal, without using RStudio.\n\nWithin the `root` user, additional system dependencies can be\ninstalled to make the image fit the needs of the user.\n\n```\ndocker exec -it bioc-3.14 bash\n```\n\nFor more information on how to use `docker-compose`, use the\n[official docker-compose reference](https://docs.docker.com/compose/reference/up/).\n\n

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\n\n\n## Modifying the images\n\nThere are two ways to modify these images:\n\n1. Making changes in a running container and then committing them\n using the `docker commit` command.\n\n\t\tdocker commit \n\n2. Using a Dockerfile to declare the changes you want to make.\n\nThe second way is the recommended way. Both ways are\n[documented here](https://docs.docker.com/userguide/dockerimages/#creating-our-own-images).\n\nExample 1:\n\n My goal is to add a python package 'tensorflow' and to install a\n Bioconductor package called 'scAlign' on top of the base docker\n image i.e bioconductor/bioconductor_docker:devel.\n\n As a first step, my Dockerfile should inherit from the\n `bioconductor/bioconductor_docker:devel` image, and build from\n there. Since all docker images are Linux environments, and this\n container is specifically 'Debian', I need some knowledge on how to\n install libraries on Linux machines.\n\n In your new `Dockerfile`, you can have the following commands\n\n\t# Docker inheritance\n\tFROM bioconductor/bioconductor_docker:devel\n\n\t# Update apt-get\n\tRUN apt-get update \\\n\t\t## Install the python package tensorflow\n\t\t&& pip install tensorflow\t\t\\\n\t\t## Remove packages in '/var/cache/' and 'var/lib'\n\t\t## to remove side-effects of apt-get update\n\t\t&& apt-get clean \\\n\t\t&& rm -rf /var/lib/apt/lists/*\n\n\t# Install required Bioconductor package\n\tRUN R -e 'BiocManager::install(\"scAlign\")'\n\n This `Dockerfile` can be built with the command, (note: you can name\n it however you want)\n\n\tdocker build -t bioconductor_docker_tensorflow:devel .\n\n This will let you use the docker image with 'tensorflow' installed and\n also `scAlign` package.\n\n\tdocker run -p 8787:8787 -e PASSWORD=bioc bioconductor_docker_tensorflow:devel\n\nExample 2:\n\n My goal is to add all the required infrastructure to be able to\n compile vignettes and knit documents into pdf files. My `Dockerfile`\n will look like the following for this requirement,\n\n\t# This docker image has LaTeX to build the vignettes\n\tFROM bioconductor/bioconductor_docker:devel\n\n\t# Update apt-get\n\tRUN apt-get update \\\n\t\t&& apt-get install -y --no-install-recommends apt-utils \\\n\t\t&& apt-get install -y --no-install-recommends \\\n\t\ttexlive \\\n\t\ttexlive-latex-extra \\\n\t\ttexlive-fonts-extra \\\n\t\ttexlive-bibtex-extra \\\n\t\ttexlive-science \\\n\t\ttexi2html \\\n\t\ttexinfo \\\n\t\t&& apt-get clean \\\n\t\t&& rm -rf /var/lib/apt/lists/*\n\n\t## Install BiocStyle\n\tRUN R -e 'BiocManager::install(\"BiocStyle\")'\n\n This `Dockerfile` can be built with the command,\n\n\tdocker build -t bioconductor_docker_latex:devel .\n\n This will let you use the docker image as needed to build and\n compile vignettes for packages.\n\n\tdocker run -p 8787:8787 -e PASSWORD=bioc bioconductor_docker_latex:devel\n\n

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\n\n\n## Singularity\n\nThe latest `bioconductor/bioconductor_docker` images are available on\nSingularity Hub as well. Singularity is a container runtime just like\nDocker, and Singularity Hub is the host registry for Singularity\ncontainers.\n\nYou can find the Singularity containers collection on this link\nhttps://singularity-hub.org/collections/3955.\n\nThese images are particularly useful on compute clusters where you\ndon't need admin access. You need to have the module `singularity`\ninstalled. See https://singularity.lbl.gov/docs-installation (contact your\nIT department when in doubt).\n\nIf you have Singularity installed on your machine or cluster are:\n\nInspect available modules\n\n\tmodule available\n\nIf Singularity is available,\n\n\tmodule load singularity\n\nPlease check this link for specific usage instructions relevant to Singularity\ncontainers and their usage https://www.rocker-project.org/use/singularity/.\n\n\n## Microsoft Azure Container Instances\n\nIf you are a Microsoft Azure user, you have an option to run your\ncontainers using images hosted on [Microsoft Container Registry](https://github.com/microsoft/ContainerRegistry).\n\n> Microsoft Container Registry (MCR) is the primary Registry for all Microsoft Published docker images that offers a reliable and trustworthy delivery of container images with a syndicated catalog\n\n\n### Using containers hosted on Microsoft Container Registry\n\nYou can learn more about the `bioconductor_docker` image hosted on\nMicosoft Container Registry\n[here](https://hub.docker.com/_/microsoft-bioconductor/).\n\nPull the `bioconductor_docker` image from Microsoft Container\nRegistry, specifying your `tag` of choice. Check\n[here](https://hub.docker.com/_/microsoft-bioconductor-bioconductor-docker)\nfor the list of tags under \"Full Tag Listing\":\n\n\tdocker pull mcr.microsoft.com/bioconductor/bioconductor_docker:\n\nTo pull the latest image:\n\n\tdocker pull mcr.microsoft.com/bioconductor/bioconductor_docker:latest\n\n**Example: Run RStudio interactively from your docker container**\n\nTo run RStudio in a web browser session, run the following and access\nit from `127.0.0.1:8787`. The default user name is \"rstudio\" and you\ncan specify your password as the example below (here, it is set to\n'bioc'):\n\n\tdocker run --name bioconductor_docker_rstudio \\\n\t\t-v ~/host-site-library:/usr/local/lib/R/host-site-library \\\n\t\t-e PASSWORD='bioc' \\\n\t\t-p 8787:8787 \\\n\t\tmcr.microsoft.com/bioconductor/bioconductor_docker:latest\n\nTo run RStudio on your terminal:\n\n\tdocker run --name bioconductor_docker_rstudio \\\n\t\t-it \\\n\t\t-v ~/host-site-library:/usr/local/lib/R/host-site-library \\\n\t\t-e PASSWORD='bioc' \\\n\t\t-p 8787:8787 \\\n\t\tmcr.microsoft.com/bioconductor/bioconductor_docker:latest R\n\n

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\n\n\n### Use Azure Container Instances to run bioconductor images on-demand on Azure\n\n[Azure Container Instances or ACI](https://azure.microsoft.com/en-us/services/container-instances/#features)\nprovide a way to run Docker containers on-demand in a managed,\nserverless Azure environment. To learn more, check out the\ndocumentation\n[here](https://docs.microsoft.com/en-us/azure/container-instances/container-instances-overview).\n\n### Run bioconductor images using ACI\n\n**Prerequisites**:\n1. [An Azure account and a\n subscription](https://docs.microsoft.com/en-us/azure/guides/developer/azure-developer-guide#understanding-accounts-subscriptions-and-billing)\n you can create resources in\n\n2. [Azure\n CLI](https://docs.microsoft.com/en-us/cli/azure/install-azure-cli?view=azure-cli-latest)\n\n3. Create a [resource\n group](https://docs.microsoft.com/en-us/azure/azure-resource-manager/management/manage-resource-groups-portal)\n within your subscription\n\nYou can run [Azure CLI or \"az cli\"\ncommands](https://docs.microsoft.com/en-us/cli/azure/?view=azure-cli-latest)\nto create, stop, restart or delete container instances running any\nbioconductor image - either official images by bioconductor or images\navailable on [Microsoft Container\nRegistry](https://hub.docker.com/_/microsoft-bioconductor). To get\nstarted, ensure you have an Azure account and a subscription or\n[create a free account](https://azure.microsoft.com/en-us/free/).\n\nFollow [this\ntutorial](https://docs.microsoft.com/en-us/azure/container-instances/container-instances-quickstart)\nto get familiar with Azure Container Instances.\n\nTo run the bioconductor image hosted on Microsoft Container Registry\nor MCR, create a new resource group in your Azure subscription. Then\nrun the following command using Azure CLI. You can customize any or\nall of the inputs. This command is adapted to run on an Ubuntu\nmachine:\n\n\taz container create \\\n\t\t--resource-group resourceGroupName \\\n\t\t--name mcr-bioconductor \\\n\t\t--image mcr.microsoft.com/bioconductor/bioconductor_docker \\\n\t\t--cpu 2 \\\n\t\t--memory 4 \\\n\t\t--dns-name-label mcr-bioconductor \\\n\t\t--ports 8787 \\\n\t\t--environment-variables 'PASSWORD'='bioc'\n\nWhen completed, run this command to get the fully qualified domain name(FQDN):\n\n\taz container show \\\n\t\t--resource-group resourceGroupName \\\n\t\t--name mcr-bioconductor \\\n\t\t--query \"{FQDN:ipAddress.fqdn,ProvisioningState:provisioningState}\" \\\n\t\t--out table\n\nHere we expose port `8787` on this publicly accessible FQDN. You may\nhave to choose a different \"dns-name-label\" to avoid conflicts. By\ndefault, the username for RStudio is \"rstudio\" (similar to the\nofficial bioconductor docker image). Here we set the password for\nRStudio to 'bioc' in the environment variable configuration. The\n`--cpu` and `--memory` (in GB) configurations can also be customized\nto your needs. By default, ACI have 1 cpu core and 1.5GB of memory\nassigned.\n\nTo learn more about what you can configure and customize when creating\nan ACI, run:\n\n\taz container create --help\n\n#### Mount Azure File Share to persist analysis data between sessions\n\nTo ensure that the data persists between different analysis sessions\nwhen using Azure Container Instances, you can use the feature to\n[mount Azure file share to your container instance](https://docs.microsoft.com/en-us/azure/container-instances/container-instances-volume-azure-files). In this example, we will create\nan ACI that mounts the \"/home/rstudio\" directory in RStudio to an\n[Azure File Share](https://docs.microsoft.com/en-us/azure/storage/files/storage-files-introduction).\n\n**Prerequisites**:\n\n1. [An Azure account and a subscription](https://docs.microsoft.com/en-us/azure/guides/developer/azure-developer-guide#understanding-accounts-subscriptions-and-billing) you can create resources in\n\n2. [Azure CLI](https://docs.microsoft.com/en-us/cli/azure/install-azure-cli?view=azure-cli-latest)\n\n3. Create a [resource group](https://docs.microsoft.com/en-us/azure/azure-resource-manager/management/manage-resource-groups-portal)\n within your subscription\n\nNow, run the following Azure CLI commands to:\n\n1. Create an [Azure\n Storage](https://docs.microsoft.com/en-us/azure/storage/common/storage-account-create?toc=%2Fazure%2Fstorage%2Fblobs%2Ftoc.json&tabs=azure-cli)\n account\n\n2. Create an [Azure file\n share](https://docs.microsoft.com/en-us/azure/storage/files/storage-how-to-use-files-cli)\n\n3. Get the [storage account\n key](https://docs.microsoft.com/en-us/cli/azure/storage/account/keys?view=azure-cli-latest)\n\n```\n# Change these four parameters as needed\nACI_PERS_RESOURCE_GROUP=resourceGroupName\nACI_PERS_STORAGE_ACCOUNT_NAME=storageAccountName\nACI_PERS_LOCATION=eastus\nACI_PERS_SHARE_NAME=fileShareName\n\n# Step1: Create the storage account with the parameters\naz storage account create \\\n\t--resource-group $ACI_PERS_RESOURCE_GROUP \\\n\t--name $ACI_PERS_STORAGE_ACCOUNT_NAME \\\n\t--location $ACI_PERS_LOCATION \\\n\t--sku Standard_LRS\n\n# Step2: Create the file share\naz storage share create \\\n\t--name $ACI_PERS_SHARE_NAME \\\n\t--account-name $ACI_PERS_STORAGE_ACCOUNT_NAME\n\n# Step3: Get the storage account key\nSTORAGE_KEY=$(az storage account keys list \\\n\t--resource-group $ACI_PERS_RESOURCE_GROUP \\\n\t--account-name $ACI_PERS_STORAGE_ACCOUNT_NAME \\\n\t--query \"[0].value\" --output tsv)\necho $STORAGE_KEY\n```\n\nHere is an example command to mount an Azure file share to an ACI running bioconductor. This command is adapted to run on an Ubuntu machine:\n\n\taz container create \\\n\t\t--resource-group resourceGroupName \\\n\t\t--name mcr-bioconductor-fs \\\n\t\t--image mcr.microsoft.com/bioconductor/bioconductor_docker \\\n\t\t--dns-name-label mcr-bioconductor-fs \\\n\t\t--cpu 2 \\\n\t\t--memory 4 \\\n\t\t--ports 8787 \\\n\t\t--environment-variables 'PASSWORD'='bioc' \\\n\t\t--azure-file-volume-account-name storageAccountName \\\n\t\t--azure-file-volume-account-key $STORAGE_KEY \\\n\t\t--azure-file-volume-share-name fileShareName \\\n\t\t--azure-file-volume-mount-path /home/rstudio\n\nWhen completed, run this command to get the fully qualified domain name or FQDN:\n\n\taz container show \\\n\t\t--resource-group resourceGroupName \\\n\t\t--name mcr-bioconductor-fs \\\n\t\t--query \"{FQDN:ipAddress.fqdn,ProvisioningState:provisioningState}\" \\\n\t\t--out table\n\nHere we expose port 8787 on this publicly accessible FQDN. You may\nhave to choose a different \"dns-name-label\" to avoid conflicts. By\ndefault, the username for RStudio is \"rstudio\" (similar to the\nofficial bioconductor docker image). Here we set the password for\nRStudio to 'bioc' in the environment variable configuration. The\n\"--cpu\" and \"--memory\" (in GB) configurations can also be customized\nto your needs. By default, ACI have 1 cpu core and 1.5GB of memory\nassigned. Here, we also mount RStudio \"/home/rstudio\" directory to a\npersistent Azure file share named \"fileShareName\" in the storage\naccount specified. 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