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nfdrug

https://github.com/bai123350/nfdrug

Science Score: 57.0%

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
    Found .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 (12.2%) to scientific vocabulary
Last synced: 6 months ago · JSON representation ·

Repository

Basic Info
  • Host: GitHub
  • Owner: bai123350
  • License: mit
  • Language: Nextflow
  • Default Branch: main
  • Size: 3.72 MB
Statistics
  • Stars: 1
  • Watchers: 1
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Created 12 months ago · Last pushed 10 months ago
Metadata Files
Readme Changelog License Citation

README.md

BioLabFree/nfdrug

Cite with Zenodo nf-test Nextflow run with conda run with docker run with singularity Launch on Seqera Platform

workflow

mermaid flowchart TB subgraph MURUNDATA subgraph take v0["samples"] end v3([DATATETCHDRUG]) v4([MUTILDATAPROCESS]) v5([MUALLMODELS]) v6([MUTRAIN]) v7([VISIABLE]) v8([SHAP]) v0 --> v3 v0 --> v4 v3 --> v4 v0 --> v5 v4 --> v5 v0 --> v6 v5 --> v6 v0 --> v7 v6 --> v7 v0 --> v8 v3 --> v8 v4 --> v8 v5 --> v8 v6 --> v8 end

Introduction

BioLabFree/nfdrug is a bioinformatics pipeline that predict drugs.

  1. prepare matrix data
  2. prepare drug data
  3. prepre protein data

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.

Now, you can run the pipeline using:

bash nextflow run nfdrug/main.nf \ -profile <docker/singularity/.../institute> \ --input samplesheet.csv \ --outdir <OUTDIR>

[!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.

Credits

BioLabFree/nfdrug was originally written by kongjd.

We thank the following people for their extensive assistance in the development of this pipeline:

Contributions and Support

If you would like to contribute to this pipeline, please see the contributing guidelines.

Citations

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

This pipeline uses code and infrastructure developed and maintained by the nf-core community, reused here under the MIT license.

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: KongJD
  • Login: bai123350
  • Kind: user
  • Location: ShangHai

Citation (CITATIONS.md) 

# open-bio/molflow: 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

- [FastQC](https://www.bioinformatics.babraham.ac.uk/projects/fastqc/)

> Andrews, S. (2010). FastQC: A Quality Control Tool for High Throughput Sequence Data [Online].

- [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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Dependencies

modules/nf-core/fastqc/meta.yml cpan
modules/nf-core/multiqc/meta.yml cpan
subworkflows/nf-core/utils_nextflow_pipeline/meta.yml cpan
subworkflows/nf-core/utils_nfcore_pipeline/meta.yml cpan
subworkflows/nf-core/utils_nfschema_plugin/meta.yml cpan
modules/local/datafetch/environment.yml pypi
modules/local/dataprocess/environment.yml pypi
  • networkx *
  • numpy *
  • pandas *
modules/local/models/environment.yml pypi
  • numpy ==1.26.4
  • scikit-learn ==1.5.2
modules/local/move/environment.yml pypi
modules/local/train/environment.yml pypi
  • matplotlib ==3.9.2
  • numpy ==1.26.4
  • scikit-learn ==1.5.2
modules/local/visiable/environment.yml pypi
  • matplotlib ==3.9.2
  • numpy ==1.26.4
  • scikit-learn ==1.5.2
  • seaborn ==0.13.1
modules/local/visshap/environment.yml pypi
  • matplotlib ==3.9.2
  • numpy ==1.26.4
  • pandas ==2.1.4
  • scikit-learn ==1.5.2
  • seaborn ==0.13.1
modules/nf-core/fastqc/environment.yml pypi
modules/nf-core/multiqc/environment.yml pypi