combinegvcfs

Joint genotyping with GLNexus

https://github.com/renzotale88/combinegvcfs

Science Score: 44.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
    Found CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
  • DOI references
    Found 7 DOI reference(s) in README
  • Academic publication links
  • Academic email domains
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  • Scientific vocabulary similarity
    Low similarity (11.7%) to scientific vocabulary
Last synced: 9 months ago · JSON representation ·

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
Created over 1 year ago · Last pushed 10 months ago
Metadata Files
Readme Changelog Contributing License Code of conduct Citation

README.md

nf-core/combinegvcfs

GitHub Actions CI Status GitHub Actions Linting StatusAWS CICite with Zenodo nf-test

Nextflow run with conda run with docker run with singularity Launch on Seqera Platform

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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 test before 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 # Finished results in specified location (defined with --outdir) .nextflow_log # Log file from Nextflow

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

  • bcftools

    Twelve 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.

  • GLNexus

    Accurate, 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

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.

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