This project contains an IRIDA plugin for a pipeline to perform AMR detection using RGI and staramr.
Please download the provided amr-detection-[version].jar from the releases page and copy to your /etc/irida/plugins directory. Now you may start IRIDA and you should see the pipeline appear in your list of pipelines.
Note: This plugin requires you to be running IRIDA version >= 21.01. Please see the IRIDA documentation for more details.
In order to use this pipeline, you will also have to install the RGI, staramr, and shovill (for assembly) Galaxy tools within your Galaxy instance. These can be found at:
| Name | Version | Galaxy Tool |
|---|---|---|
| RGI | 5.2.1 |
https://toolshed.g2.bx.psu.edu/view/card/rgi/84bd24ac33fd |
| staramr | 0.9.1+galaxy0 |
https://toolshed.g2.bx.psu.edu/view/nml/staramr/4d83eccf5f81 |
| shovill | 1.1.0+galaxy1 |
https://toolshed.g2.bx.psu.edu/view/iuc/shovill/ad80238462c1 |
If you run into issues when installing RGI into Galaxy related to dependency resolution issues in Conda, then the following may help install RGI 5.2.1 into Galaxy:
Using the Conda installation that Galaxy uses (which is likely different from the system's Conda installation), run the following prior to installing the RGI tool in Galaxy:
conda install -c conda-forge -c bioconda -c defaults mamba -y
mamba create -c iuc -c conda-forge -c bioconda -c defaults --no-channel-priority --name __rgi@5.2.1 rgi=5.2.1 -y
This code will install mamba into the Conda environment used by Galaxy, which is better at performing dependency resolution, and then it will create an RGI Conda environment named __rgi@5.2.1 with RGI v5.2.1 installed within it. This environment will be named in a way that Galaxy expects, which is important for the next step.
Attempt to install RGI v5.2.1 in Galaxy as normal. Behind the scences, Galaxy will recognize that the previously created RGI conda environment exists and it will use that existing installation.
Finally, the RGI database will need to be installed manually. On the Galaxy admin page, navigate to the "Local Data" section. You should find the "RGI Database Builder" button below the "Installed Data Managers" section. Click the "RGI Database Builder" button and you will be brought to a new page where you can start a job to download and build the database. You should update the "Database name" section (ex: "CARD") before starting the job. Once you hit the execute button, Galaxy will start to download and build the database.
This tutorial shows how to run the AMR Detection pipeline in IRIDA.
The pipeline requires as input paired-end sequence reads in FASTQ format. We will be using Illumina MiSeq data from a sample of Campylobacter jejuni for this tutorial with run ID SRR8914694. Paired-end fastq files can be downloaded from https://www.ebi.ac.uk/ena/data/view/SRR8914694 (the FASTQ files (FTP) links). A collection of additional example data can be found in the IRIDA Sample Data package.
Once samples are created for the data and the files are uploaded, you can select the samples you wish to run and add them to the cart by clicking the Add to Cart button.
Once you have selected your samples, you can click on the Cart button to move to selecting a pipeline.
Once inside the cart, you should see a card for the AMR Detection pipeline.
Please click the Select button to proceed with the pipeline.
Once the pipeline is selected, the next page provides an overview of all the input files, as well as the option to modify parameters.
Please make sure the Save AMR detection results to Project Line List Metadata is selected so that results get saved to the Line List. Also, please click the Customize button so that we can modify the PointFinder parameters.
In particular, you may want to modify the Scan for point mutations using the selected PointFinder database parameter, changing the value to campylobacter. If you which to completely disable searching the PointFinder database, you can instead set this to disabled (the default value).
If you know the organism you may also want to set the lower/upper bounds for the genome length. This only impacts the output of the quality module (which checks if the assembled genome is within these bounds). In this case the organism is Campylobacter jejuni so let's set the lower bound to 1400000 and upper bound to 1900000.
Once all your parameters are set, you can click the Ready to Launch? button to launch the pipeline.
To monitor the status of the launched pipeline, please select the Analyses > Your Analyses menu.
From here, you can monitor the status of your pipeline.
Once the analysis pipeline is finished, you can view the analysis results in your browser or download the files to your machine.
These results show you both the staramr and RGI AMR results on the data, assembled with shovill. The staramr results are all contained within a single Excel file shown here, which lists the detected antimicrobial resistance genes, MLST sequence type, plasmid incompatibility factors among other information. For details on how to interpret these, please see the documentation of the respective projects.
If you selected the Save AMR detection results to Project Line List Metadata option when launching the pipeline, then both the predicted AMR genes and drug resistances will be integrated into the IRIDA Line List/Metadata table as shown below.
To build this plugin yourself, you must first install IRIDA to your local Maven repository. Please make sure you are installing the IRIDA version defined in the irida.version.compiletime property in the pom.xml file (e.g., 21.01). Or, alternatively, please update the IRIDA dependency version in the pom.xml file.
To install the IRIDA libraries to a local Maven repository, please run the following from within the IRIDA project (the irida/ directory):
mvn clean install -DskipTestsOnce IRIDA is installed, you may build the pipeline plugin by running the following in this project's directory (the irida-plugin-amr-detection/ directory):
mvn clean packageThis should produce a target/*.jar file, which can be copied into /etc/irida/plugins/.
Copyright 2019 Government of Canada
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this work except in compliance with the License. You may obtain a copy of the License at:
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.