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https://github.com/cdcgov/irma

IRMA (the Iterative Refinement Meta-Assembler) is a highly configurable and adaptive tool for virus genome assembly.

https://github.com/cdcgov/irma

Science Score: 57.0%

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cdc-influenza-division ncird-id
Last synced: 6 months ago · JSON representation ·

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IRMA (the Iterative Refinement Meta-Assembler) is a highly configurable and adaptive tool for virus genome assembly.

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cdc-influenza-division ncird-id
Created about 1 year ago · Last pushed 6 months ago
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Readme Changelog License Citation

README.md

IRMA - the Iterative Refinement Meta-Assembler

IRMA is a highly configurable next-generation sequencing assembly pipeline for virus genomes. Seed references are refined and edited as reads are matched, sorted, and aligned across virus genomes or gene segments. More information can be found on the IRMA website or you can read the manuscript. If you use IRMA in a paper, please cite us.

Visit the CHANGELOG to see recent changes.

Table of contents

Usage

IRMA takes a module-configuration name, one or two fastq, and a project name. The project name can be a full path. For example:

```bash Usage: (PAIRED-END): IRMA [path/to/] options: IRMA [path/to/] [options]

Options: --external-config|-c ```

More usage information: https://wonder.cdc.gov/amd/flu/irma/run.html

Installation and Requirements

We recommend a multi-core machine with no fewer than 8 cores (16 or more threads work best) and at least 16 GB of RAM. IRMA runtime is impacted by the number of cores available on a machine. In addition software requirements include:

  • Perl 5.16
  • R 3.6+
  • BASH 3+
  • Linux: RHEL 8+ or any recent Ubuntu like Bookworm
  • OR macOS 10.14 on intel, macOS 11 on arm64 (Rosetta 2 required for LABEL)

Via Archive

Download the latest archive via our releases page. Use of wget or curl for downloads is recommended for macOS to preserve functionality.

1) Unzip the archive containing IRMA. 2) Move the package to your desired location and add the folder to your PATH - Note: IRMA_RES and IRMA must be in the same folder. 3) IRMA is now installed. To test it from the package folder, execute:

bash ./IRMA FLU tests/test2.fastq.gz test_project

Via Container

Simply run:

```bash

From Github

docker run --rm -itv $(pwd):/data ghcr.io/cdcgov/irma:latest IRMA # more args

From Dockerhub

docker run --rm -itv $(pwd):/data docker/cdcgov/irma:latest LABEL # more args ```

Via MIRA

For a GUI interface, please visit MIRA. For usage with nextflow consider MIRA-NF. MIRA provides more end-to-end functionality out-of-the-box by integrating other components and providing extra summaries.

Third Party Software

We aggregate and provide builds of 3rd party software for execution at runtime with IRMA. Similarly, still more third-party software is co-distributed with LABEL for runtime with IRMA. You may install or obtain your own copies and IRMA will detect them, but the user will be required to test for compatibility.

In IRMA proper

Co-distributed under LABEL

  • GNU Parallel
  • SHOGUN version 1.1.0 (2.1+ is not compatible)
    • Artifacts: shogun (cmdline_static)
    • Exception: apple/arm64 requires Rosetta2
    • Purpose: executes the SVM decision phase.
    • License: GPL v3
  • SAM version 3.5
    • Artifacts: align2model, hmmscore, modelfromalign
    • Purpose: build HMM profiles, score sequences for evaluation
    • License: Custom academic/government, not-for-profit, redistributed with permission

[!WARNING] Note that blat and SAM is redistributed with permission but their terms exclude commerical use without a license. If you are a commercial entity, you might need to reach out to the respective authors (see example blat-license and sam-license) to obtain a license for commercial use.

Contributing

New feature integration is mainly being moved to the irma-core project (supported by Zoe), which is a mandatory component of IRMA as of v1.3.0. The IRMA repo itself will continue to address fixes needed for the Perl, R, and BASH code base, albeit some pieces may be obviated in future versions by IRMA-core or other changes. This repo will also continue to be responsible for data updates and other module artifacts and for the overall build and release.

Semantic Versioning

We elect to define semantic versioning for IRMA explicitly. Some of our choices may differ from other interpretations of SemVer; our have been made for practicality reasons.

Major

  • Breaking changes to the command line interface (CLI)
  • Breaking changes to data output that are typically processed downstream (tables, FASTA, BAM, etc.)
  • Breaking changes to configuration format or changes to a configuration that would cause IRMA to abort
  • Breaking changes to supported data inputs

Minor

  • Adding new, non-breaking features
  • Changes that break undocumented/unintended behaviors for generating data without altering output data formats or structure
  • Changes in figures or figure generation
  • Changes in module or program configuration defaults
  • Re-mapping or obviating an existing configuration field without breaking anything defined in Major.
  • Changes to the structure of saved, intermediate data (as some people rely on this)

Patch

  • Bug fixes
  • Minor performance improvements
  • Non-breaking updates to dependencies
  • Log or error improvements
  • Changes in config file defaults
  • Changes in module data meant to correct a performance or correctness issue
  • Removing an experimental configuration field without causing an abort

Notices

Contact Info

For direct correspondence on the project, feel free to contact: Samuel S. Shepard, Centers for Disease Control and Prevention or reach out to the IRMA contributors.

Public Domain Standard Notice

This repository constitutes a work of the United States Government and is not subject to domestic copyright protection under 17 USC § 105. This repository is in the public domain within the United States, and copyright and related rights in the work worldwide are waived through the CC0 1.0 Universal public domain dedication. All contributions to this repository will be released under the CC0 dedication. By submitting a pull request you are agreeing to comply with this waiver of copyright interest.

License Standard Notice

The repository utilizes code licensed under the terms of the Apache Software License and therefore is licensed under ASL v2 or later. This source code in this repository is free: you can redistribute it and/or modify it under the terms of the Apache Software License version 2, or (at your option) any later version. This source code in this repository is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the Apache Software License for more details. You should have received a copy of the Apache Software License along with this program. If not, see: http://www.apache.org/licenses/LICENSE-2.0.html. The source code forked from other open source projects will inherit its license.

Privacy Standard Notice

This repository contains only non-sensitive, publicly available data and information. All material and community participation is covered by the Disclaimer. For more information about CDC's privacy policy, please visit http://www.cdc.gov/other/privacy.html.

Contributing Standard Notice

Anyone is encouraged to contribute to the repository by forking and submitting a pull request. (If you are new to GitHub, you might start with a basic tutorial.) By contributing to this project, you grant a world-wide, royalty-free, perpetual, irrevocable, non-exclusive, transferable license to all users under the terms of the Apache Software License v2 or later.

All comments, messages, pull requests, and other submissions received through CDC including this GitHub page may be subject to applicable federal law, including but not limited to the Federal Records Act, and may be archived. Learn more at http://www.cdc.gov/other/privacy.html.

Records Management Standard Notice

This repository is not a source of government records, but is a copy to increase collaboration and collaborative potential. All government records will be published through the CDC web site.

Additional Standard Notices

Please refer to CDC's Template Repository for more information about contributing to this repository, public domain notices and disclaimers, and code of conduct.

Owner

  • Name: Centers for Disease Control and Prevention
  • Login: CDCgov
  • Kind: organization
  • Email: data@cdc.gov
  • Location: Atlanta, GA

CDC's collaborative software projects to protect America from health, safety, and security threats, both foreign and in the U.S.

Citation (CITATION.bib) 

@article{Shepard:2016aa,
  abstract      = {BACKGROUND: Deep sequencing makes it possible to observe low-frequency viral variants and sub-populations with greater accuracy and sensitivity than ever before. Existing platforms can be used to multiplex a large number of samples; however, analysis of the resulting data is complex and involves separating barcoded samples and various read manipulation processes ending in final assembly. Many assembly tools were designed with larger genomes and higher fidelity polymerases in mind and do not perform well with reads derived from highly variable viral genomes. Reference-based assemblers may leave gaps in viral assemblies while de novo assemblers may struggle to assemble unique genomes.
                   RESULTS: The IRMA (iterative refinement meta-assembler) pipeline solves the problem of viral variation by the iterative optimization of read gathering and assembly. As with all reference-based assembly, reads are included in assembly when they match consensus template sets; however, IRMA provides for on-the-fly reference editing, correction, and optional elongation without the need for additional reference selection. This increases both read depth and breadth. IRMA also focuses on quality control, error correction, indel reporting, variant calling and variant phasing. In fact, IRMA's ability to detect and phase minor variants is one of its most distinguishing features. We have built modules for influenza and ebolavirus. We demonstrate usage and provide calibration data from mixture experiments. Methods for variant calling, phasing, and error estimation/correction have been redesigned to meet the needs of viral genomic sequencing.
                   CONCLUSION: IRMA provides a robust next-generation sequencing assembly solution that is adapted to the needs and characteristics of viral genomes. The software solves issues related to the genetic diversity of viruses while providing customized variant calling, phasing, and quality control. IRMA is freely available for non-commercial use on Linux and Mac OS X and has been parallelized for high-throughput computing.},
  author        = {\textbf{Samuel S. Shepard} and Meno, Sarah and Bahl, Justin and Wilson, Malania M and Barnes, John and Neuhaus, Elizabeth},
  date-added    = {2016-09-12 16:56:21 +0000},
  date-modified = {2016-09-12 16:56:21 +0000},
  doi           = {10.1186/s12864-016-3030-6},
  journal       = {BMC Genomics},
  journal-full  = {BMC genomics},
  keywords      = {Deep sequencing; Ebola; High throughput; Influenza; NGS; Public health; Surveillance},
  pages         = {708},
  pmc           = {PMC5011931},
  pmid          = {27595578},
  pst           = {epublish},
  title         = {Viral deep sequencing needs an adaptive approach: IRMA, the iterative refinement meta-assembler},
  volume        = {17},
  year          = {2016},
  bdsk-url-1    = {http://dx.doi.org/10.1186/s12864-016-3030-6}
}

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