createpanelofnormals

Create panel of normals for Mutect2 & CNVKit

https://github.com/qbic-pipelines/createpanelofnormals

Science Score: 31.0%

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
  • .zenodo.json file
  • DOI references
    Found 10 DOI reference(s) in README
  • Academic publication links
  • Academic email domains
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (11.7%) to scientific vocabulary
Last synced: 10 months ago · JSON representation ·

Repository

Create panel of normals for Mutect2 & CNVKit

Basic Info
  • Host: GitHub
  • Owner: qbic-pipelines
  • License: mit
  • Language: Nextflow
  • Default Branch: master
  • Homepage:
  • Size: 2.44 MB
Statistics
  • Stars: 0
  • Watchers: 1
  • Forks: 1
  • Open Issues: 0
  • Releases: 0
Created almost 3 years ago · Last pushed almost 3 years ago
Metadata Files
Readme Changelog Contributing License Code of conduct Citation

README.md

qbic-pipelines/createpanelofnormals qbic-pipelines/createpanelofnormals

Cite with Zenodo

Nextflow run with conda run with docker run with singularity Launch on Nextflow Tower

Introduction

qbic-pipelines/createpanelofnormals is a bioinformatics pipeline for creating a panel of normals for Mutect2 following these instructions and CNVKit using cnvkit batch.

  1. Variant calling on normal samples with (GATK4 Mutect2)
  2. Create GenomicsDB
  3. Combine normal calls with CreateSomaticPanelOfNormals
  4. Group all normal files and run CNVKit batch with the parameters -n, -t, -m, and -y if (--assume_male is set). > Disclaimer: not tested for panel or exome data. There might be need for more flags or input files.
  5. Collect versions in (MultiQC)

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.

First, prepare a samplesheet with your input data that looks as follows:

samplesheet.csv:

csv sample,cram,crai sample1,test.cram,test.cram.crai

Each row represents one sample.

Now, you can run the pipeline using:

bash nextflow run qbic-pipelines/createpanelofnormals \ -profile <docker/singularity/.../institute> \ --input samplesheet.csv \ --outdir <OUTDIR>

To get an overview over all available parameters, run:

bash nextflow run qbic-pipelines/createpanelofnormals --help

Warning: Please provide pipeline parameters via the CLI or Nextflow -params-file option. Custom config files including those provided by the -c Nextflow option can be used to provide any configuration except for parameters; see docs.

For more details and further functionality, please refer to the usage documentation and the parameter documentation.

Pipeline output

For more details about the output files and reports, please refer to the output documentation.

Credits

qbic-pipelines/createpanelofnormals was originally written by FriederikeHanssen.

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 by opening an issue.

Citations

If you use qbic-pipelines/createpanelofnormals for your analysis, please cite it using the following doi: 10.5281/zenodo.671039381

An extensive list of references for the tools used by the pipeline can be found in the CITATIONS.md file.

The pipeline is currently maintained at QBiC and not an nf-core pipeline since it has not undergone nf-core community review. It was created using the nf-core template and integrates their institutional profiles as well as many other resources. If you use this pipeline, please cite them 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: QBiC (qbic-pipelines)
  • Login: qbic-pipelines
  • Kind: organization
  • Email: support@qbic.zendesk.com
  • Location: University of Tübingen

Bioinformatics analysis pipelines at QBiC

Citation (CITATIONS.md)

# nf-core/createpanelofnormals: 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


- [CNVKIT](https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1004873)

  > Talevich E, Shain AH, Botton T, Bastian BC (2016) CNVkit: Genome-Wide Copy Number Detection and Visualization from Targeted DNA Sequencing. PLoS Comput Biol 12(4): e1004873. doi: 10.1371/journal.pcbi.1004873. PubMed PMID: 27100738. PubMed Central PMCID: PMC4839673.

- [GATK](https://pubmed.ncbi.nlm.nih.gov/20644199/)

  > McKenna A, Hanna M, Banks E, et al.: The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res. 2010 Sep;20(9):1297-303. doi: 10.1101/gr.107524.110. Epub 2010 Jul 19. PubMed PMID: 20644199; PubMed Central PMCID: PMC2928508.

- [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)

  > 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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.github/workflows/awsfulltest.yml actions
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  • seqeralabs/action-tower-launch v2 composite
.github/workflows/awstest.yml actions
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.github/workflows/branch.yml actions
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.github/workflows/ci.yml actions
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.github/workflows/clean-up.yml actions
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.github/workflows/fix-linting.yml actions
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.github/workflows/linting.yml actions
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  • actions/upload-artifact v3 composite
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.github/workflows/linting_comment.yml actions
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modules/nf-core/custom/dumpsoftwareversions/meta.yml cpan
modules/nf-core/fastqc/meta.yml cpan
modules/nf-core/multiqc/meta.yml cpan
pyproject.toml pypi