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proteomicstmt

nf-core pipeline for proteomics TMT analysis

https://github.com/jpfeuffer/proteomicstmt

Science Score: 44.0%

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Repository

nf-core pipeline for proteomics TMT analysis

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  • Host: GitHub
  • Owner: jpfeuffer
  • Default Branch: main
  • Size: 25.5 MB
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Created over 5 years ago · Last pushed almost 5 years ago
Metadata Files
Readme Code of conduct Citation

README.md

image

Proteomics Tandem Mass Tags quantification (TMT) analysis pipeline using OpenMS and MSstats, with feature quantification, feature summarization, quality control and group-based statistical analysis..

Introduction

The pipeline is built using Nextflow, a workflow tool to run tasks across multiple compute infrastructures in a very portable manner. It comes with docker containers making installation trivial and results highly reproducible.

Quick Start

  1. Install nextflow

  2. Install either Docker or Singularity for full pipeline reproducibility (please only use Conda as a last resort; see docs)

  3. Download the pipeline and test it on a minimal dataset with a single command:

    bash nextflow run nf-core/proteomicsTMT -profile test,<docker/singularity/conda/institute>

    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 either docker or singularity and set the appropriate execution settings for your local compute environment.

  4. Start running your own analysis!

    bash nextflow run nf-core/proteomicsTMT \ -profile <docker/singularity/conda/institute> \ --input '*.mzml' \ --database 'myProteinDB.fasta' \ --expdesign 'myDesign.tsv'

Citation

If you use nf-core/proteomicsTMT for your analysis, please cite it using the following doi: 10.5281/zenodo.XXXXXX

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. ReadCube: Full Access Link

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

Owner

  • Name: Julianus Pfeuffer
  • Login: jpfeuffer
  • Kind: user
  • Location: Berlin
  • Company: FU Berlin

Citation (CITATIONS.md) 

# nf-core/proteomicslfq: Citations

## Pipeline tools

* [Nextflow](https://www.ncbi.nlm.nih.gov/pubmed/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.

* [OpenMS](https://www.ncbi.nlm.nih.gov/pubmed/27575624/)
  > Röst HL., Sachsenberg T., Aiche S., Bielow C., Weisser H., Aicheler F., Andreotti S., Ehrlich HC., Gutenbrunner P., Kenar E., Liang X., Nahnsen S., Nilse L., Pfeuffer J., Rosenberger G., Rurik M., Schmitt U., Veit J., Walzer M., Wojnar D., Wolski WE., Schilling O., Choudhary JS, Malmström L., Aebersold R., Reinert K., Kohlbacher O. (2016). OpenMS: a flexible open-source software platform for mass spectrometry data analysis. Nature methods, 13(9), 741–748. doi: 10.1038/nmeth.3959. PubMed PMID: 27575624; PubMed Central PMCID: PMC5617107.

* [MSstats](https://www.ncbi.nlm.nih.gov/pubmed/24794931/)
  > Choi M., Chang CY., Clough T., Broudy D., Killeen T., MacLean B., Vitek O. (2014). MSstats: an R package for statistical analysis of quantitative mass spectrometry-based proteomic experiments. Bioinformatics (Oxford, England), 30(17), 2524–2526. doi: 10.1093/bioinformatics/btu305. PubMed PMID: 24794931.

* [ThermoRawFileParser](https://www.ncbi.nlm.nih.gov/pubmed/31755270/)
  > Hulstaert N., Shofstahl J., Sachsenberg T., Walzer M., Barsnes H., Martens L., Perez-Riverol, Y. (2020). ThermoRawFileParser: Modular, Scalable, and Cross-Platform RAW File Conversion. Journal of proteome research, 19(1), 537–542. doi: 10.1021/acs.jproteome.9b00328. PubMed PMID: 31755270

* [Comet](https://www.ncbi.nlm.nih.gov/pubmed/23148064/)
  > Eng JK., Jahan TA., Hoopmann MR. (2013). Comet: an open-source MS/MS sequence database search tool. Proteomics, 13(1), 22–24. doi: 10.1002/pmic.201200439. PubMed PMID: 23148064

* [MS-GF+](https://www.ncbi.nlm.nih.gov/pubmed/25358478/)
  > Kim S., Pevzner PA. (2014). MS-GF+ makes progress towards a universal database search tool for proteomics. Nature communications, 5, 5277. doi: 10.1038/ncomms6277. PubMed PMID: 25358478; PubMed Central PMCID: PMC5036525

* [PTXQC](https://www.ncbi.nlm.nih.gov/pubmed/26653327/)
  > Bielow C., Mastrobuoni G., Kempa S. (2016). Proteomics Quality Control: Quality Control Software for MaxQuant Results. Journal of proteome research, 15(3), 777–787. doi: 10.1021/acs.jproteome.5b00780. PubMed PMID: 26653327

## Software packaging/containerisation tools

* [BioContainers](https://www.ncbi.nlm.nih.gov/pubmed/28379341/)
  > da Veiga Leprevost F, Grüning BA, Alves Aflitos S, Röst HL, Uszkoreit J, Barsnes H, Vaudel M, Moreno P, Gatto L, Weber J, Bai M, Jimenez RC, Sachsenberg T, Pfeuffer J, Vera Alvarez R, 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.

* [Singularity](https://www.ncbi.nlm.nih.gov/pubmed/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.

* [Conda](https://www.ncbi.nlm.nih.gov/pubmed/29967506/)
  > Grüning B., Dale R., Sjödin A., Chapman BA., Rowe J., Tomkins-Tinch CH., Valieris R., Köster J., Bioconda Team (2018). Bioconda: sustainable and comprehensive software distribution for the life sciences. Nature methods, 15(7), 475–476. doi: 10.1038/s41592-018-0046-7. PubMed PMID: 29967506.

* [Docker](https://www.docker.com/)
  > Merkel D. (2014). Docker: lightweight Linux containers for consistent development and deployment. Linux journal, 2014(239), 2.

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Dependencies

environment.yml conda
  • bioconductor-msstats 3.20.1.*
  • fonts-conda-ecosystem 1.*
  • markdown 3.2.2.*
  • openms 2.6.0.*
  • openms-thirdparty 2.6.0.*
  • pygments 2.7.1.*
  • pymdown-extensions 8.0.1.*
  • python 3.8.5.*
  • r-ptxqc 1.0.5.*
  • sdrf-pipelines 0.0.9.*
  • xorg-libxt 1.2.0.*