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proteomicslfq

Proteomics label-free quantification (LFQ) analysis pipeline

https://github.com/nf-core/proteomicslfq

Science Score: 54.0%

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 10 DOI reference(s) in README
  • ○
    Academic publication links
  • ✓
    Committers with academic emails
    5 of 12 committers (41.7%) from academic institutions
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (15.2%) to scientific vocabulary

Keywords

label-free-quantification nextflow nf-core openms pipeline proteomics workflow

Keywords from Contributors

airr b-cell immcantation immunorepertoire taxonomic-profiling taxonomic-classification rrna qiime2 pacbio microbiome
Last synced: 6 months ago · JSON representation ·

Repository

Proteomics label-free quantification (LFQ) analysis pipeline

Basic Info
Statistics
  • Stars: 36
  • Watchers: 157
  • Forks: 21
  • Open Issues: 29
  • Releases: 1
Topics
label-free-quantification nextflow nf-core openms pipeline proteomics workflow
Created almost 7 years ago · Last pushed about 1 year ago
Metadata Files
Readme Changelog Contributing License Code of conduct Citation

README.md

nf-core/proteomicslfq

Proteomics label-free quantification (LFQ) analysis pipeline using OpenMS and MSstats, with feature quantification, feature summarization, quality control and group-based statistical analysis..

GitHub Actions CI Status GitHub Actions Linting Status Nextflow Cite with Zenodo

install with bioconda Docker Get help on Slack

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/proteomicslfq -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/proteomicslfq \ -profile <docker/singularity/conda/institute> \ --input '*.mzml' \ --database 'myProteinDB.fasta' \ --expdesign 'myDesign.tsv'

See usage docs for all of the available options when running the pipeline. Or configure the pipeline via nf-core launch from the web or the command line.

Documentation

The nf-core/proteomicslfq pipeline comes with documentation about the pipeline which you can read at https://nf-co.re/proteomicslfq or partly find in the docs/ directory.

It performs conversion to indexed mzML, database search (with multiple search engines), re-scoring (with e.g. Percolator), merging, FDR filtering, modification localization with Luciphor2 (e.g. phospho-sites), protein inference and grouping as well as label-free quantification by either spectral counting or feature-based alignment and integration. Downstream processing includes statistical post-processing with MSstats and quality control with PTXQC. For more info, see the output docs.

Credits

nf-core/proteomicslfq was originally written by Julianus Pfeuffer, Lukas Heumos, Leon Bichmann, Timo Sachsenberg, Yasset Perez-Riverol.

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 #proteomicslfq channel (you can join with this invite).

Citation

If you use nf-core/proteomicslfq 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: nf-core
  • Login: nf-core
  • Kind: organization
  • Email: core@nf-co.re

A community effort to collect a curated set of analysis pipelines built using Nextflow.

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.

GitHub Events

Total
  • Issues event: 10
  • Watch event: 1
  • Issue comment event: 2
  • Push event: 1
  • Fork event: 1
Last Year
  • Issues event: 10
  • Watch event: 1
  • Issue comment event: 2
  • Push event: 1
  • Fork event: 1

Committers

Last synced: over 2 years ago

All Time
  • Total Commits: 375
  • Total Committers: 12
  • Avg Commits per committer: 31.25
  • Development Distribution Score (DDS): 0.437
Past Year
  • Commits: 0
  • Committers: 0
  • Avg Commits per committer: 0.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
Julianus Pfeuffer j****r@f****e 211
jpfeuffer p****r@i****e 82
yperez y****l@g****m 30
Julianus Pfeuffer p****r@a****e 21
Zethson l****s@p****t 21
Leon Bichmann b****n@a****e 2
MaxUlysse m****a@g****m 2
nf-core-bot c****e@n****e 2
runner r****r@f****0 1
Julianus Pfeuffer p****r@a****e 1
Gisela Gabernet Garriga g****t@g****m 1
Zethson l****s@g****m 1
Committer Domains (Top 20 + Academic)
abinode04.informatik.uni-tuebingen.de: 2 nf-co.re: 1 posteo.net: 1 abidocker.informatik.uni-tuebingen.de: 1 informatik.uni-tuebingen.de: 1 fu-berlin.de: 1

Issues and Pull Requests

Last synced: almost 2 years ago

All Time
  • Total issues: 35
  • Total pull requests: 72
  • Average time to close issues: 3 months
  • Average time to close pull requests: 30 days
  • Total issue authors: 19
  • Total pull request authors: 9
  • Average comments per issue: 3.69
  • Average comments per pull request: 1.29
  • Merged pull requests: 37
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 2
  • Pull requests: 8
  • Average time to close issues: 4 days
  • Average time to close pull requests: about 1 month
  • Issue authors: 2
  • Pull request authors: 2
  • Average comments per issue: 4.0
  • Average comments per pull request: 1.13
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
  • jpfeuffer (12)
  • hendrikweisser (4)
  • ypriverol (2)
  • timosachsenberg (2)
  • ncarrut (2)
  • fabianegli (2)
  • JannikSchneider12 (1)
  • luozhy88 (1)
  • rolivella (1)
  • matteopilz (1)
  • BenSamy2020 (1)
  • apeltzer (1)
  • FriederikeHanssen (1)
  • Jokendo-collab (1)
  • jen-reeve (1)
Pull Request Authors
  • jpfeuffer (39)
  • nf-core-bot (29)
  • ypriverol (2)
  • KevinMenden (2)
  • aelezi01 (1)
  • timosachsenberg (1)
  • tillenglert (1)
  • Zethson (1)
  • maxulysse (1)
Top Labels
Issue Labels
enhancement (6) documentation (1) low-priority (1) good first issue (1) high-priority (1)
Pull Request Labels

Dependencies

.github/workflows/awsfulltest.yml actions
  • goanpeca/setup-miniconda v1.0.2 composite
.github/workflows/awstest.yml actions
  • goanpeca/setup-miniconda v1.0.2 composite
.github/workflows/branch.yml actions
  • mshick/add-pr-comment v1 composite
.github/workflows/ci.yml actions
  • actions/checkout v2 composite
  • actions/upload-artifact v1 composite
  • technote-space/get-diff-action v1 composite
.github/workflows/linting.yml actions
  • actions/checkout v2 composite
  • actions/checkout v1 composite
  • actions/setup-node v1 composite
  • actions/setup-python v1 composite
  • actions/upload-artifact v2 composite
.github/workflows/push_dockerhub.yml actions
  • actions/checkout v2 composite
Dockerfile docker
  • nfcore/base 1.10.2 build
dev/Dockerfile docker
  • openms/executables latest build
environment.yml pypi