Getting Started

IRIDA is the official bioinformatics platform used for public health genomics at the Public Health Agency of Canada (PHAC). IRIDA has been used since 2012 for national surveillance of foodborne disease (PulseNet) in the pan-Canadian Public Health Laboratory Network (CPHLN), and in other surveillance programs employing genomic epidemiology. Instances of IRIDA have been installed across the globe (e.g. the U.S., Switzerland, Singapore, South Africa and Italy), including a demonstration version currently available in the Genomics Virtual Lab toolkit which supports a wide range of clinical research groups across Australia and around the world.

Testing Out the IRIDA Platform

The IRIDA platform is composed of several different applications. Most users of IRIDA will use the web interface for managing and organizing their sequencing data, and for launching analytical pipelines on their data. Some advanced users of IRIDA might want to export their data to a separate instance of Galaxy or directly to the Linux command-line interface for more in-depth analysis. Administrative users and laboratory technicians will run tools for adding data to IRIDA from sequencing instruments. Several options are available for users wishing to test the functionality of the IRIDA platform:

  1. Public Instance: Simon Fraser University hosts a public instance of IRIDA, currently for demonstration purposes, at Accounts for the public instance can be acquired by contacting [email protected].

  2. Install an Instance of IRIDA: IRIDA instances can be installed in any high performance computing environment. IRIDA requires a working installation of Galaxy to be configured before the web interface can submit workflows for execution. Once you’ve installed and configured Galaxy, you can install the IRIDA web interface. Guides for installing and configuring Galaxy and the IRIDA web interface can be found here.

  3. Virtual Machine (VM): A fully-configured virtual appliance for Oracle VirtualBox is available for demonstration purposes. You can download the complete package here (26 GB download).  The virtual appliance is currently configured to use 8 CPU cores and requires at least 8GB of RAM. You may reduce the number of CPU cores allocated to the virtual appliance, however, we do not recommend that you use any less than 4 CPU cores. Once you start the virtual appliance, you can connect to IRIDA in several ways: using your web browser, using an uploader tool, or using SSH. Instructions for using the VM can be found here.


  1. Tutorial Documentation
  2. User
  3. Administrator
  4. Getting data into IRIDA
  5. Analyzing your data with IRIDA
  6. Getting your data out of IRIDA

Getting data into IRIDA

You can load sequencing data into IRIDA in two different ways:

  1. Using the web interface
  2. Using the uploader tool

The web interface upload feature is useful if you only want to add data to IRIDA for one or two samples. If you want to load data into IRIDA in bulk (especially if you’re a sequencing facility!) you should use the uploader tool to transfer your data.

Once you create your Projects and Samples, you can upload your sequence data.

Watch this video to see how you can create a Sample file:

  Watch this video to see how you can upload sequence data:

Analyzing your data with IRIDA

IRIDA has several different built-in pipelines for analyzing your data:

  1. Assembling your sequencing data
  2. Whole-genome SNV Phylogeny
  3. Salmonella in-silico Typing (SISTR)
  4. MentaLiST cgMLST
  5. RefSeqMasher
  6. Antimicrobial Resistance (AMR) Gene Detection
  7. Biohansel

Watch this video to see how to launch an analysis pipeline:

Getting your data out of IRIDA

You will sometimes want to be able to get data out of IRIDA, if you want to share your data with an external collaborator, or if you want to run more in-depth analysis than what the analytical tools in IRIDA provide. You can use the tutorials below to get your data out of IRIDA:

  1. Sharing projects
  2. Sharing some data from a project
  3. Exporting data to Galaxy
  4. Exporting data to the command-line
  5. Exporting data to NCBI’s Sequence Read Archive