magmap
Best-practice analysis pipeline for mapping reads to a (large) collections of genomes
Science Score: 57.0%
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✓CITATION.cff file
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✓codemeta.json file
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✓.zenodo.json file
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✓DOI references
Found 10 DOI reference(s) in README -
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○Scientific vocabulary similarity
Low similarity (12.7%) to scientific vocabulary
Keywords
Repository
Best-practice analysis pipeline for mapping reads to a (large) collections of genomes
Basic Info
- Host: GitHub
- Owner: nf-core
- License: mit
- Language: Nextflow
- Default Branch: master
- Homepage: https://nf-co.re/magmap
- Size: 3.27 MB
Statistics
- Stars: 7
- Watchers: 182
- Forks: 4
- Open Issues: 10
- Releases: 0
Topics
Metadata Files
README.md
Introduction
nf-core/magmap is a bioinformatics best-practice analysis pipeline for nf-core/magmap is a bioinformatics best-practice analysis pipeline for mapping reads to a (large) collections of genomes..
The pipeline is built using Nextflow, a workflow tool to run tasks across multiple compute infrastructures in a very portable manner. It uses Docker/Singularity containers making installation trivial and results highly reproducible. The Nextflow DSL2 implementation of this pipeline uses one container per process which makes it much easier to maintain and update software dependencies. Where possible, these processes have been submitted to and installed from nf-core/modules in order to make them available to all nf-core pipelines, and to everyone within the Nextflow community!
On release, automated continuous integration tests run the pipeline on a full-sized dataset on the AWS cloud infrastructure. This ensures that the pipeline runs on AWS, has sensible resource allocation defaults set to run on real-world datasets, and permits the persistent storage of results to benchmark between pipeline releases and other analysis sources. The results obtained from the full-sized test can be viewed on the nf-core website.
Pipeline summary
Quick Start
Install
Nextflow(>=21.10.3)Install any of
Docker,Singularity,Podman,ShifterorCharliecloudfor full pipeline reproducibility (please only useCondaas a last resort; see docs)Download the pipeline and test it on a minimal dataset with a single command:
console nextflow run nf-core/magmap -profile test,YOURPROFILENote that some form of configuration will be needed so that Nextflow knows how to fetch the required software. This is usually done in the form of a config profile (
YOURPROFILEin the example command above). You can chain multiple config profiles in a comma-separated string.- The pipeline comes with config profiles called
docker,singularity,podman,shifter,charliecloudandcondawhich instruct the pipeline to use the named tool for software management. For example,-profile test,docker. - Please check nf-core/configs to see if a custom config file to run nf-core pipelines already exists for your Institute. If so, you can simply use
-profile <institute>in your command. This will enable eitherdockerorsingularityand set the appropriate execution settings for your local compute environment. - If you are using
singularityand are persistently observing issues downloading Singularity images directly due to timeout or network issues, then you can use the--singularity_pull_docker_containerparameter to pull and convert the Docker image instead. Alternatively, you can use thenf-core downloadcommand to download images first, before running the pipeline. Setting theNXF_SINGULARITY_CACHEDIRorsingularity.cacheDirNextflow options enables you to store and re-use the images from a central location for future pipeline runs. - If you are using
conda, it is highly recommended to use theNXF_CONDA_CACHEDIRorconda.cacheDirsettings to store the environments in a central location for future pipeline runs.
- The pipeline comes with config profiles called
Start running your own analysis!
console nextflow run nf-core/magmap -profile <docker/singularity/podman/shifter/charliecloud/conda/institute> --input samplesheet.csv --genome GRCh37
Documentation
The nf-core/magmap pipeline comes with documentation about the pipeline usage, parameters and output.
Credits
nf-core/magmap was originally written by Danilo Di Leo, Emelie Nilsson and Daniel Lundin.
We thank the following people for their extensive assistance in the development of this pipeline:
Contributions and Support
If you would like to contribute to this pipeline, please see the contributing guidelines.
For further information or help, don't hesitate to get in touch on the Slack #magmap channel (you can join with this invite).
Citations
An extensive list of references for the tools used by the pipeline can be found in the CITATIONS.md file.
You can cite the nf-core publication as follows:
The nf-core framework for community-curated bioinformatics pipelines.
Philip Ewels, Alexander Peltzer, Sven Fillinger, Harshil Patel, Johannes Alneberg, Andreas Wilm, Maxime Ulysse Garcia, Paolo Di Tommaso & Sven Nahnsen.
Nat Biotechnol. 2020 Feb 13. doi: 10.1038/s41587-020-0439-x.
Owner
- Name: nf-core
- Login: nf-core
- Kind: organization
- Email: core@nf-co.re
- Website: http://nf-co.re
- Twitter: nf_core
- Repositories: 84
- Profile: https://github.com/nf-core
A community effort to collect a curated set of analysis pipelines built using Nextflow.
Citation (CITATIONS.md)
# nf-core/magmap: Citations
## [nf-core](https://pubmed.ncbi.nlm.nih.gov/32055031/)
> Ewels PA, Peltzer A, Fillinger S, Patel H, Alneberg J, Wilm A, Garcia MU, Di Tommaso P, Nahnsen S. The nf-core framework for community-curated bioinformatics pipelines. Nat Biotechnol. 2020 Mar;38(3):276-278. doi: 10.1038/s41587-020-0439-x. PubMed PMID: 32055031.
## [Nextflow](https://pubmed.ncbi.nlm.nih.gov/28398311/)
> Di Tommaso P, Chatzou M, Floden EW, Barja PP, Palumbo E, Notredame C. Nextflow enables reproducible computational workflows. Nat Biotechnol. 2017 Apr 11;35(4):316-319. doi: 10.1038/nbt.3820. PubMed PMID: 28398311.
## Pipeline tools
* [FastQC](https://www.bioinformatics.babraham.ac.uk/projects/fastqc/)
* [MultiQC](https://pubmed.ncbi.nlm.nih.gov/27312411/)
> Ewels P, Magnusson M, Lundin S, Käller M. MultiQC: summarize analysis results for multiple tools and samples in a single report. Bioinformatics. 2016 Oct 1;32(19):3047-8. doi: 10.1093/bioinformatics/btw354. Epub 2016 Jun 16. PubMed PMID: 27312411; PubMed Central PMCID: PMC5039924.
## Software packaging/containerisation tools
* [Anaconda](https://anaconda.com)
> Anaconda Software Distribution. Computer software. Vers. 2-2.4.0. Anaconda, Nov. 2016. Web.
* [Bioconda](https://pubmed.ncbi.nlm.nih.gov/29967506/)
> Grüning B, Dale R, Sjödin A, Chapman BA, Rowe J, Tomkins-Tinch CH, Valieris R, Köster J; Bioconda Team. Bioconda: sustainable and comprehensive software distribution for the life sciences. Nat Methods. 2018 Jul;15(7):475-476. doi: 10.1038/s41592-018-0046-7. PubMed PMID: 29967506.
* [BioContainers](https://pubmed.ncbi.nlm.nih.gov/28379341/)
> da Veiga Leprevost F, Grüning B, Aflitos SA, Röst HL, Uszkoreit J, Barsnes H, Vaudel M, Moreno P, Gatto L, Weber J, Bai M, Jimenez RC, Sachsenberg T, Pfeuffer J, Alvarez RV, Griss J, Nesvizhskii AI, Perez-Riverol Y. BioContainers: an open-source and community-driven framework for software standardization. Bioinformatics. 2017 Aug 15;33(16):2580-2582. doi: 10.1093/bioinformatics/btx192. PubMed PMID: 28379341; PubMed Central PMCID: PMC5870671.
* [Docker](https://dl.acm.org/doi/10.5555/2600239.2600241)
* [Singularity](https://pubmed.ncbi.nlm.nih.gov/28494014/)
> Kurtzer GM, Sochat V, Bauer MW. Singularity: Scientific containers for mobility of compute. PLoS One. 2017 May 11;12(5):e0177459. doi: 10.1371/journal.pone.0177459. eCollection 2017. PubMed PMID: 28494014; PubMed Central PMCID: PMC5426675.
GitHub Events
Total
- Issues event: 20
- Watch event: 4
- Delete event: 8
- Issue comment event: 44
- Push event: 23
- Pull request review event: 35
- Pull request review comment event: 40
- Pull request event: 50
- Create event: 5
Last Year
- Issues event: 20
- Watch event: 4
- Delete event: 8
- Issue comment event: 44
- Push event: 23
- Pull request review event: 35
- Pull request review comment event: 40
- Pull request event: 50
- Create event: 5
Issues and Pull Requests
Last synced: 6 months ago
All Time
- Total issues: 13
- Total pull requests: 21
- Average time to close issues: 5 months
- Average time to close pull requests: 28 days
- Total issue authors: 4
- Total pull request authors: 4
- Average comments per issue: 0.38
- Average comments per pull request: 1.48
- Merged pull requests: 13
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 12
- Pull requests: 21
- Average time to close issues: 4 months
- Average time to close pull requests: 28 days
- Issue authors: 4
- Pull request authors: 4
- Average comments per issue: 0.42
- Average comments per pull request: 1.48
- Merged pull requests: 13
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- danilodileo (14)
- erikrikarddaniel (8)
- geweaa (2)
- johnne (1)
- amizeranschi (1)
Pull Request Authors
- danilodileo (31)
- nf-core-bot (11)
- erikrikarddaniel (8)
- jfy133 (1)
- fabianegli (1)
Top Labels
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Dependencies
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