Data

Tools

Indexes

Applications

Experiments

Open Source Science

prepngs

A pipeline to pre-process raw NGS data for downstream reuse across various pipelines

https://github.com/gallvp/prepngs

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 10 DOI reference(s) in README
  • ○
    Academic publication links
  • ○
    Academic email domains
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (9.9%) to scientific vocabulary
Last synced: 6 months ago · JSON representation ·

Repository

A pipeline to pre-process raw NGS data for downstream reuse across various pipelines

Basic Info
  • Host: GitHub
  • Owner: GallVp
  • License: mit
  • Language: Nextflow
  • Default Branch: dev
  • Homepage:
  • Size: 245 KB
Statistics
  • Stars: 1
  • Watchers: 1
  • Forks: 1
  • Open Issues: 1
  • Releases: 0
Created over 1 year ago · Last pushed over 1 year ago
Metadata Files
Readme Changelog Contributing License Citation

README.md

GitHub Actions CI Status GitHub Actions Linting StatusCite with Zenodo nf-test

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

Introduction

gallvp/prepngs is a bioinformatics pipeline that pre-processes NGS data for downstream reuse across various pipelines.

```mermaid %%{init: { 'theme': 'base', 'themeVariables': { 'fontSize': '12px", 'primaryColor': '#9A6421', 'primaryTextColor': '#ffffff', 'primaryBorderColor': '#9A6421', 'lineColor': '#B180A8', 'secondaryColor': '#455C58', 'tertiaryColor': '#ffffff' } }}%%

flowchart LR samplesheet(samplesheet.csv) ==> BAM2FASTQ samplesheet ==> FASTQC

BAM2FASTQ ==> FASTQC FASTQC ==> FASTP FASTP ==> FASTQC2[FASTQC]

FASTP ==> CAT CAT ==> FQ2FA

CAT ==> fqout(FastQ) FQ2FA ==> faout(Fasta)

FASTQC2 ==> multiqcout(MultiQC)

subgraph Outputs[" "] multiqcout fqout faout end

classDef bk fill:#0000 class Outputs bk ```

  1. BAM to FastQ (PBTK, optional)
  2. Raw read QC (FastQC)
  3. Adapter trimming (FASTP)
  4. Trimmed read QC (FastQC)
  5. Cat trimmed reads by group (cat, optional)
  6. Convert trimmed reads to Fasta (Seqkit, optional)
  7. Present QC (MultiQC)

Usage

Refer to usage, parameters and output documents for details.

[!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,group,reads_1,reads_2 test1,,r1.fastq.gz,r2.fastq.gz test2,group1,sampleA.ccs.bam test3,group1,sampleC.ccs.bam

Each row represents a sample with a single fastq/bam file (single-end) or a pair of fastq files (paired end). group column is optional. When present, it is used to concatenate the samples.

[!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.

Now, you can run the pipeline using:

bash nextflow run gallvp/prepngs \ -profile <docker/singularity/.../institute> \ --input samplesheet.csv \ --outdir <OUTDIR>

Plant&Food Users

Download the pipeline to your /workspace/$USER folder. Change the parameters defined in the pfr/params.json file. Submit the pipeline to SLURM for execution.

bash sbatch ./pfr_prepngs

Credits

gallvp/prepngs was originally written by Usman Rashid.

The pipeline uses nf-core modules contributed by following authors:

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: Usman Rashid
  • Login: GallVp
  • Kind: user
  • Location: Auckland

Bioinformatics Developer at The New Zealand Institute for Plant and Food Research.

Citation (CITATIONS.md) 

# gallvp/prepngs: 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].

- [fastp](https://github.com/OpenGene/fastp)

  > Chen S, Zhou Y, Chen Y, Gu J. 2018. fastp: an ultra-fast all-in-one FASTQ preprocessor, Bioinformatics, Volume 34, Issue 17, 01 September 2018, Pages i884–i890, <https://doi.org/10.1093/bioinformatics/bty560>

- [SeqKit](https://github.com/shenwei356/seqkit)

  > Shen W, Le S, Li Y, Hu F. 2016. SeqKit: A Cross-Platform and Ultrafast Toolkit for FASTA/Q File Manipulation. PLoS ONE 11(10): e0163962. <https://doi.org/10.1371/journal.pone.0163962>

- [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.

GitHub Events

Total
Last Year