Science Score: 44.0%
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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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Found 7 DOI reference(s) in README -
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○Scientific vocabulary similarity
Low similarity (11.7%) to scientific vocabulary
Repository
Joint genotyping with GLNexus
Basic Info
- Host: GitHub
- Owner: RenzoTale88
- License: mit
- Language: Nextflow
- Default Branch: main
- Size: 247 KB
Statistics
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
- Releases: 2
Metadata Files
README.md
Introduction
nf-core/combinegvcfs is a bioinformatics pipeline that takes a set of GVCF files and consolidates them in a single multi-sample VCF file.
Usage
[!NOTE] If you are new to Nextflow and nf-core, please refer to this page on how to set-up Nextflow. Make sure to test your setup with
-profile testbefore running the workflow on actual data.
Introduction
This workflow will consolidate a set of GVCF files using GLNexus. The workflow will perform the consolidation chromosome-by-chromosome, pooling the small contigs (below --chunk_size), minimizing the number of processes and their run times.
The GLNexus configuration can be specified with --glnexus_config. If a user needs to provide a custom configuration file, they can do so using the options --glnexus_config custom --glnexus_config_file <PATH/TO/INPUT/CONFIG.yml>.
Samplesheet input
You will need to create a samplesheet with information about the samples you would like to analyse before running the pipeline. Use this parameter to specify its location. It has to be a comma-separated file with 3 columns, and a header row as shown in the examples below.
bash
--input '[path to samplesheet file]'
The sample identifiers have to be unique, i.e. one sample per line. The file should have exactly three columns, specifying the sample name and the path to the respective GVCF and TBI files:
csv title="samplesheet.csv"
sample,gvcf,tbi
SAMPLE1,AEG588A1_S1_L002_R1_001.g.vcf.gz,AEG588A1_S1_L002_R2_001.g.vcf.gz.tbi
SAMPLE2,AEG588A1_S1_L003_R1_001.g.vcf.gz,AEG588A1_S1_L003_R2_001.g.vcf.gz.tbi
SAMPLE3,AEG588A1_S1_L004_R1_001.g.vcf.gz,AEG588A1_S1_L004_R2_001.g.vcf.gz.tbi
An example samplesheet has been provided with the pipeline.
Running the pipeline
The typical command for running the pipeline is as follows:
bash
nextflow run nf-core/combinegvcfs --input ./samplesheet.csv --outdir ./results --fasta GRCh37.fa -profile docker
This will launch the pipeline with the docker configuration profile. See below for more information about profiles.
Note that the pipeline will create the following files in your working directory:
```bash
work # Directory containing the nextflow working files
Other nextflow hidden files, eg. history of pipeline runs and old logs.
```
If you wish to repeatedly use the same parameters for multiple runs, rather than specifying each flag in the command, you can specify these in a params file.
Pipeline settings can be provided in a yaml or json file via -params-file <file>.
:::warning
Do not use -c <file> to specify parameters as this will result in errors. Custom config files specified with -c must only be used for tuning process resource specifications, other infrastructural tweaks (such as output directories), or module arguments (args).
:::
The above pipeline run specified with a params file in yaml format:
bash
nextflow run nf-core/combinegvcfs -profile docker -params-file params.yaml
with:
yaml title="params.yaml"
input: './samplesheet.csv'
outdir: './results/'
fasta: 'GRCh37.fa'
<...>
You can also generate such YAML/JSON files via nf-core/launch.
Updating the pipeline
When you run the above command, Nextflow automatically pulls the pipeline code from GitHub and stores it as a cached version. When running the pipeline after this, it will always use the cached version if available - even if the pipeline has been updated since. To make sure that you're running the latest version of the pipeline, make sure that you regularly update the cached version of the pipeline:
bash
nextflow pull nf-core/combinegvcfs
Pipeline output
To see the results of an example test run with a full size dataset refer to the results tab on the nf-core website pipeline page. For more details about the output files and reports, please refer to the output documentation.
Credits
nf-core/combinegvcfs was originally written by Andrea Talenti.
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 #combinegvcfs channel (you can join with this invite).
Citations
bcftoolsTwelve years of SAMtools and BCFtools.
Petr Danecek, James K Bonfield, Jennifer Liddle, John Marshall, Valeriu Ohan, Martin O Pollard, Andrew Whitwham, Thomas Keane, Shane A McCarthy, Robert M Davies, Heng Li.
Gigascience (2021) 10(2):giab008.
GLNexusAccurate, scalable cohort variant calls using DeepVariant and GLnexus.
Taedong Yun, Helen Li, Pi-Chuan Chang, Michael F Lin, Andrew Carroll, Cory Y McLean.
Bioinformatics, Volume 36, Issue 24, December 2020, Pages 5582–5589.
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: Andrea Talenti
- Login: RenzoTale88
- Kind: user
- Repositories: 1
- Profile: https://github.com/RenzoTale88
Citation (CITATIONS.md)
# nf-core/combinegvcfs: 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 ## 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) > Merkel, D. (2014). Docker: lightweight linux containers for consistent development and deployment. Linux Journal, 2014(239), 2. 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
- Release event: 2
- Push event: 4
- Public event: 1
- Create event: 1
Last Year
- Release event: 2
- Push event: 4
- Public event: 1
- Create event: 1
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