Data

Tools

Indexes

Applications

Experiments

Open Source Science

nanoseq

Nanopore demultiplexing, QC and alignment pipeline

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

Science Score: 67.0%

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 7 DOI reference(s) in README
  • ○
    Academic publication links
  • ✓
    Committers with academic emails
    8 of 26 committers (30.8%) from academic institutions
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (13.0%) to scientific vocabulary

Keywords

alignment demultiplexing nanopore nextflow nf-core pipeline qc workflow

Keywords from Contributors

atac-seq chromatin-accessibiity
Last synced: 6 months ago · JSON representation ·

Repository

Nanopore demultiplexing, QC and alignment pipeline

Basic Info
  • Host: GitHub
  • Owner: nf-core
  • License: mit
  • Language: Nextflow
  • Default Branch: master
  • Homepage: https://nf-co.re/nanoseq
  • Size: 6.92 MB
Statistics
  • Stars: 203
  • Watchers: 152
  • Forks: 98
  • Open Issues: 55
  • Releases: 6
Topics
alignment demultiplexing nanopore nextflow nf-core pipeline qc workflow
Created over 6 years ago · Last pushed 8 months ago
Metadata Files
Readme Changelog Contributing License Code of conduct Citation

README.md

nf-core/nanoseq nf-core/nanoseq

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

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

Get help on SlackFollow on TwitterWatch on YouTube

Introduction

nfcore/nanoseq is a bioinformatics analysis pipeline for Nanopore DNA/RNA sequencing data that can be used to perform basecalling, demultiplexing, QC, alignment, and downstream analysis.

The pipeline is built using Nextflow, a workflow tool to run tasks across multiple compute infrastructures in a very portable manner. It uses Docker/Singularity containers making installation trivial and results highly reproducible. The Nextflow DSL2 implementation of this pipeline uses one container per process which makes it much easier to maintain and update software dependencies. Where possible, these processes have been submitted to and installed from nf-core/modules in order to make them available to all nf-core pipelines, and to everyone within the Nextflow community!

On release, automated continuous integration tests run the pipeline on a full-sized dataset obtained from the Singapore Nanopore Expression Consortium on the AWS cloud infrastructure. This ensures that the pipeline runs on AWS, has sensible resource allocation defaults set to run on real-world datasets, and permits the persistent storage of results to benchmark between pipeline releases and other analysis sources. The results obtained from the full-sized test can be viewed on the nf-core website.

Pipeline Summary

  1. Demultiplexing (qcat; optional)
  2. Raw read cleaning (NanoLyse; optional)
  3. Raw read QC (NanoPlot, FastQC)
  4. Alignment (GraphMap2 or minimap2)
    • Both aligners are capable of performing unspliced and spliced alignment. Sensible defaults will be applied automatically based on a combination of the input data and user-specified parameters
    • Each sample can be mapped to its own reference genome if multiplexed in this way
    • Convert SAM to co-ordinate sorted BAM and obtain mapping metrics (samtools)
  5. Create bigWig (BEDTools, bedGraphToBigWig) and bigBed (BEDTools, bedToBigBed) coverage tracks for visualisation
  6. DNA specific downstream analysis:
  7. RNA specific downstream analysis:
    • Transcript reconstruction and quantification (bambu or StringTie2)
      • bambu performs both transcript reconstruction and quantification
      • When StringTie2 is chosen, each sample can be processed individually and combined. After which, featureCounts will be used for both gene and transcript quantification.
    • Differential expression analysis (DESeq2 and/or DEXSeq)
    • RNA modification detection (xpore and/or m6anet)
    • RNA fusion detection (JAFFAL)
  8. Present QC for raw read and alignment results (MultiQC)

Functionality Overview

A graphical overview of suggested routes through the pipeline depending on the desired output can be seen below.

nf-core/nanoseq metro map

Quick Start

  1. Install Nextflow (>=22.10.1)

  2. Install any of Docker, Singularity (you can follow this tutorial), Podman, Shifter or Charliecloud for full pipeline reproducibility (you can use Conda both to install Nextflow itself and also to manage software within pipelines. Please only use it within pipelines as a last resort; see docs).

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

console nextflow run nf-core/nanoseq -profile test,YOURPROFILE

Note that some form of configuration will be needed so that Nextflow knows how to fetch the required software. This is usually done in the form of a config profile (YOURPROFILE in the example command above). You can chain multiple config profiles in a comma-separated string.

  • The pipeline comes with config profiles called docker, singularity, podman, shifter, charliecloud and conda which instruct the pipeline to use the named tool for software management. For example, -profile test,docker.
  • 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.
  • If you are using singularity and are persistently observing issues downloading Singularity images directly due to timeout or network issues, then you can use the --singularity_pull_docker_container parameter to pull and convert the Docker image instead. Alternatively, you can use the nf-core download command to download images first, before running the pipeline. Setting the NXF_SINGULARITY_CACHEDIR or singularity.cacheDir Nextflow options enables you to store and re-use the images from a central location for future pipeline runs.
  • If you are using conda, it is highly recommended to use the NXF_CONDA_CACHEDIR or conda.cacheDir settings to store the environments in a central location for future pipeline runs.
  1. Start running your own analysis!

Documentation

The nf-core/nanoseq pipeline comes with documentation about the pipeline usage, parameters and output.

bash nextflow run nf-core/nanoseq \ --input samplesheet.csv \ --protocol DNA \ --barcode_kit SQK-PBK004 \ -profile <docker/singularity/podman/institute>

See usage docs for all of the available options when running the pipeline.

An example input samplesheet for performing both basecalling and demultiplexing can be found here.

Credits

nf-core/nanoseq was originally written by Chelsea Sawyer and Harshil Patel from The Bioinformatics & Biostatistics Group for use at The Francis Crick Institute, London. Other primary contributors include Laura Wratten, Ying Chen, Yuk Kei Wan and Jonathan Goeke from the Genome Institute of Singapore, Christopher Hakkaart from Institute of Medical Genetics and Applied Genomics, Germany, and Johannes Alneberg and Franziska Bonath from SciLifeLab, Sweden.

Many thanks to others who have helped out along the way too, including (but not limited to): @crickbabs, @AnnaSyme, @ekushele.

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 Slack (you can join with this invite).

Citations

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

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.

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/nanoseq: Citations

## [nf-core](https://www.ncbi.nlm.nih.gov/pubmed/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.

## [SGNEx](https://www.biorxiv.org/content/10.1101/2021.04.21.440736v1.abstract)

> Chen, Y., Davidson, N. M., Wan, Y. K., Patel, H., Yao, F., Low, H. M., ... & SG-NEx consortium. (2021). A systematic benchmark of Nanopore long read RNA sequencing for transcript level analysis in human cell lines. BioRxiv, 2021-04.

## [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.

## Pipeline tools

- [bambu](https://www.biorxiv.org/content/10.1101/2022.11.14.516358v2.abstract)

  > Chen, Y., Sim, A. D., Wan, Y. K., Yeo, K., Lee, J. J. X., Ling, M. H., ... & Göke, J. (2022). Context-aware transcript quantification from long read RNA-seq data with Bambu. bioRxiv, 2022-11.

- [BEDTools](https://www.ncbi.nlm.nih.gov/pubmed/20110278/)

  > Quinlan AR, Hall IM. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics. 2010 Mar 15;26(6):841-2. doi: 10.1093/bioinformatics/btq033. Epub 2010 Jan 28. PubMed PMID: 20110278; PubMed Central PMCID: PMC2832824.

- [cuteSV](https://pubmed.ncbi.nlm.nih.gov/32746918/)

  > Jiang T, Liu Y, Jiang Y, Li J, Gao Y, Cui Z, Liu Y, Liu B, Wang Y. Long-read-based human genomic structural variation detection with cuteSV. Genome Biol. 2020 Aug 3;21(1):189. doi: 10.1186/s13059-020-02107-y. PMID: 32746918; PMCID: PMC7477834.

- [DeepVariant](https://pubmed.ncbi.nlm.nih.gov/30247488/)

  > Poplin R, Chang PC, Alexander D, Schwartz S, Colthurst T, Ku A, Newburger D, Dijamco J, Nguyen N, Afshar PT, Gross SS, Dorfman L, McLean CY, DePristo MA. A universal SNP and small-indel variant caller using deep neural networks. Nat Biotechnol. 2018 Nov;36(10):983-987. doi: 10.1038/nbt.4235. Epub 2018 Sep 24. PMID: 30247488.

- [featureCounts](https://www.ncbi.nlm.nih.gov/pubmed/24227677/)

  > Liao Y, Smyth GK, Shi W. featureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics. 2014 Apr 1;30(7):923-30. doi: 10.1093/bioinformatics/btt656. Epub 2013 Nov 13. PubMed PMID: 24227677.

- [GraphMap](https://pubmed.ncbi.nlm.nih.gov/27079541/)

  > Sović I, Šikić M, Wilm A, Fenlon SN, Chen S, Nagarajan N. Fast and sensitive mapping of nanopore sequencing reads with GraphMap. Nat Commun. 2016 Apr 15;7:11307. doi: 10.1038/ncomms11307. PMID: 27079541; PMCID: PMC4835549.

- [JAFFAL](https://doi.org/10.1186/s13059-021-02588-5)

  > Davidson NM, Chen Y, Sadras T, Ryland GL, Blombery P, Ekert PG, Göke J, Oshlack A. JAFFAL: detecting fusion genes with long-read transcriptome sequencing. Genome Biol. 2022 Jan 6;23(1):10. doi: 10.1186/s13059-021-02588-5. PMID: 34991664; PMCID: PMC8739696.

- [m6anet](https://pubmed.ncbi.nlm.nih.gov/36357692/)

  > Hendra, C., Pratanwanich, P. N., Wan, Y. K., Goh, W. S., Thiery, A., & Göke, J. (2022). Detection of m6A from direct RNA sequencing using a multiple instance learning framework. Nature Methods, 1-9. PMID: 36357692; PMCID: PMC9718678.

- [PEPPER-Margin-DeepVariant](https://pubmed.ncbi.nlm.nih.gov/34725481/)

  > Shafin K, Pesout T, Chang PC, Nattestad M, Kolesnikov A, Goel S, Baid G, Kolmogorov M, Eizenga JM, Miga KH, Carnevali P, Jain M, Carroll A, Paten B. Haplotype-aware variant calling with PEPPER-Margin-DeepVariant enables high accuracy in nanopore long-reads. Nat Methods. 2021 Nov;18(11):1322-1332. doi: 10.1038/s41592-021-01299-w. Epub 2021 Nov 1. PMID: 34725481; PMCID: PMC8571015.

- [Minimap2](https://pubmed.ncbi.nlm.nih.gov/29750242/)

  > Li H. Minimap2: pairwise alignment for nucleotide sequences. Bioinformatics. 2018 Sep 15;34(18):3094-3100. doi: 10.1093/bioinformatics/bty191. PMID: 29750242; PMCID: PMC6137996.

- [Medaka](https://github.com/nanoporetech/medaka)

- [MultiQC](https://www.ncbi.nlm.nih.gov/pubmed/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.

- [NanoLyse](https://pubmed.ncbi.nlm.nih.gov/29547981/)

  > De Coster, W., D’Hert, S., Schultz, D. T., Cruts, M., & Van Broeckhoven, C. (2018). NanoPack: visualizing and processing long-read sequencing data. Bioinformatics, 34(15), 2666-2669. PubMed PMID: 29547981; PubMed Central PMCID: PMC6061794.

- [NanoPlot](https://pubmed.ncbi.nlm.nih.gov/29547981/)

  > De Coster W, D'Hert S, Schultz DT, Cruts M, Van Broeckhoven C. NanoPack: visualizing and processing long-read sequencing data. Bioinformatics. 2018 Aug 1;34(15):2666-2669. doi: 10.1093/bioinformatics/bty149. PubMed PMID: 29547981; PubMed Central PMCID: PMC6061794.

- [qcat](https://github.com/nanoporetech/qcat)

- [SAMtools](https://www.ncbi.nlm.nih.gov/pubmed/19505943/)

  > Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, Marth G, Abecasis G, Durbin R; 1000 Genome Project Data Processing Subgroup. The Sequence Alignment/Map format and SAMtools. Bioinformatics. 2009 Aug 15;25(16):2078-9. doi: 10.1093/bioinformatics/btp352. Epub 2009 Jun 8. PubMed PMID: 19505943; PubMed Central PMCID: PMC2723002.

- [Sniffles](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5990442/)

  > Sedlazeck FJ, Rescheneder P, Smolka M, Fang H, Nattestad M, von Haeseler A, Schatz MC. Accurate detection of complex structural variations using single-molecule sequencing. Nat Methods. 2018 Jun;15(6):461-468. doi: 10 1038/s41592-018-0001-7. Epub 2018 Apr 30. PMID: 29713083; PMCID: PMC5990442.

- [StringTie2](https://www.ncbi.nlm.nih.gov/pubmed/31842956/)

  > Kovaka S, Zimin AV, Pertea GM, Razaghi R, Salzberg SL, Pertea M. Transcriptome assembly from long-read RNA-seq alignments with StringTie2 Genome Biol. 2019 Dec 16;20(1):278. doi: 10.1186/s13059-019-1910-1. PubMed PMID: 31842956; PubMed Central PMCID: PMC6912988.

- [UCSC tools](https://www.ncbi.nlm.nih.gov/pubmed/20639541/)

  > Kent WJ, Zweig AS, Barber G, Hinrichs AS, Karolchik D. BigWig and BigBed: enabling browsing of large distributed datasets. Bioinformatics. 2010 Sep 1;26(17):2204-7. doi: 10.1093/bioinformatics/btq351. Epub 2010 Jul 17. PubMed PMID: 20639541; PubMed Central PMCID: PMC2922891.

- [xPore](https://doi.org/10.1038/s41587-021-00949-w)
  > Pratanwanich PN, Yao F, Chen Y, Koh CWQ, Wan YK, Hendra C, Poon P, Goh YT, Yap PML, Chooi JY, Chng WJ, Ng SB, Thiery A, Goh WSS, Göke J. Identification of differential RNA modifications from nanopore direct RNA sequencing with xPore. Nat Biotechnol. 2021 Nov;39(11):1394-1402. doi: 10.1038/s41587-021-00949-w. Epub 2021 Jul 19. PMID: 34282325.

## R packages

- [R](https://www.R-project.org/)

  > R Core Team (2017). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria.

- [bambu](https://bioconductor.org/packages/release/bioc/html/bambu.html)

  > Chen Y, Goeke J, Wan YK (2020). bambu: Reference-guided isoform reconstruction and quantification for long read RNA-Seq data. R package version 1.0.0.

- [BSgenome](https://bioconductor.org/packages/release/bioc/html/BSgenome.html)

  > Pagès H (2020). BSgenome: Software infrastructure for efficient representation of full genomes and their SNPs. doi: 10.18129/B9.bioc.BSgenome.

- [DESeq2](https://www.ncbi.nlm.nih.gov/pubmed/25516281/)

  > Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014;15(12):550. PubMed PMID: 25516281; PubMed Central PMCID: PMC4302049.

- [DEXSeq](https://pubmed.ncbi.nlm.nih.gov/22722343/)

  > Anders S, Reyes A, Huber W. Detecting differential usage of exons from RNA-seq data. Genome Res. 2012 Oct;22(10):2008-17. doi: 10.1101/gr.133744.111. Epub 2012 Jun 21. PubMed PMID: 22722343; PubMed Central PMCID: PMC3460195.

- [DRIMSeq](https://pubmed.ncbi.nlm.nih.gov/28105305/)

  > Nowicka M, Robinson MD. DRIMSeq: a Dirichlet-multinomial framework for multivariate count outcomes in genomics. F1000Res. 2016 Jun 13;5:1356. doi: 10.12688/f1000research.8900.2. PubMed PMID: 28105305; PubMed Central PMCID: PMC5200948.

- [stageR](https://pubmed.ncbi.nlm.nih.gov/28784146/)
  > Van den Berge K, Soneson C, Robinson MD, Clement L. stageR: a general stage-wise method for controlling the gene-level false discovery rate in differential expression and differential transcript usage. Genome Biol. 2017 Aug 7;18(1):151. doi: 10.1186/s13059-017-1277-0. PubMed PMID: 28784146; PubMed Central PMCID: PMC5547545.

## 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)

- [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
  • Issues event: 20
  • Watch event: 26
  • Delete event: 26
  • Issue comment event: 26
  • Push event: 43
  • Pull request review comment event: 1
  • Pull request review event: 4
  • Pull request event: 36
  • Fork event: 20
  • Create event: 20
Last Year
  • Issues event: 20
  • Watch event: 26
  • Delete event: 26
  • Issue comment event: 26
  • Push event: 43
  • Pull request review comment event: 1
  • Pull request review event: 4
  • Pull request event: 36
  • Fork event: 20
  • Create event: 20

Committers

Last synced: over 2 years ago

All Time
  • Total Commits: 1,316
  • Total Committers: 26
  • Avg Commits per committer: 50.615
  • Development Distribution Score (DDS): 0.582
Past Year
  • Commits: 60
  • Committers: 7
  • Avg Commits per committer: 8.571
  • Development Distribution Score (DDS): 0.633
Top Committers
Name Email Commits
drpatelh d****l@g****m 550
Yuk Kei Wan 4****a@u****m 255
lwratten z****9@u****u 79
Chelsea c****r@g****m 69
Chris Hakkaart c****t@m****e 60
yuukiiwa y****6@a****u 58
Yuk Kei Wan y****6@j****u 57
Laura Wratten 3****n@u****m 44
Chen Ying c****g@g****g 33
nf-core-bot c****e@n****e 22
Chris Hakkaart c****t@s****o 22
Christopher Hakkaart a****1@i****e 11
Harshil Patel d****h@u****m 9
lwratten l****a@G****l 9
ekushele e****h@g****m 7
Johannes Alneberg j****g@s****e 7
Harshil Patel d****h@g****m 5
Venkat Malladi v****i@m****m 5
Johannes Alneberg a****g@k****e 4
MaxUlysse m****a@g****m 3
christopher-hakkaart c****t@m****e 2
runner r****r@f****0 1
yukkei y****i@y****n 1
Daniel Schreyer 2****S@s****k 1
kevinmenden k****n@t****e 1
sawyerc s****c@c****g 1
Committer Domains (Top 20 + Academic)
med.uni-tuebingen.de: 2 ca170.camp.thecrick.org: 1 t-online.de: 1 student.gla.ac.uk: 1 yukkeis-mini.lan: 1 kth.se: 1 microsoft.com: 1 scilifelab.se: 1 imgag.de: 1 seqera.io: 1 nf-co.re: 1 gis.a-star.edu.sg: 1 jhu.edu: 1 alumni.jh.edu: 1 unsw.edu.au: 1

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 49
  • Total pull requests: 89
  • Average time to close issues: 4 months
  • Average time to close pull requests: 20 days
  • Total issue authors: 39
  • Total pull request authors: 15
  • Average comments per issue: 1.65
  • Average comments per pull request: 1.19
  • Merged pull requests: 50
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 13
  • Pull requests: 18
  • Average time to close issues: about 11 hours
  • Average time to close pull requests: about 2 months
  • Issue authors: 8
  • Pull request authors: 7
  • Average comments per issue: 0.08
  • Average comments per pull request: 0.5
  • Merged pull requests: 3
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
  • mlgosh (6)
  • Eric-CH-Chen (2)
  • nick-youngblut (2)
  • FranBonath (2)
  • xmeng (2)
  • matthewstuartedwards (2)
  • benbfly (2)
  • sheucke (2)
  • Salome-Brunon (1)
  • ekushele (1)
  • christopher-hakkaart (1)
  • jlandry69 (1)
  • jen-reeve (1)
  • fbndr98 (1)
  • junaruga (1)
Pull Request Authors
  • yuukiiwa (41)
  • nf-core-bot (23)
  • christopher-hakkaart (19)
  • tzvi909 (3)
  • Salome-Brunon (2)
  • ekushele (1)
  • maxulysse (1)
  • nourmahfel (1)
  • matthewstuartedwards (1)
  • tahirdme (1)
  • mazzalab (1)
  • eduard-watchmaker (1)
  • DSchreyer (1)
  • julietmWM (1)
  • jonathangoeke (1)
Top Labels
Issue Labels
bug (29) enhancement (20) invalid (1)
Pull Request Labels
bug (4) enhancement (1)

Dependencies

.github/workflows/awsfulltest.yml actions
  • nf-core/tower-action v3 composite
.github/workflows/awstest.yml actions
  • nf-core/tower-action v3 composite
.github/workflows/branch.yml actions
  • mshick/add-pr-comment v1 composite
.github/workflows/ci.yml actions
  • actions/checkout v2 composite
.github/workflows/fix-linting.yml actions
  • actions/checkout v3 composite
  • actions/setup-node v2 composite
.github/workflows/linting.yml actions
  • actions/checkout v2 composite
  • actions/setup-node v2 composite
  • actions/setup-python v3 composite
  • actions/upload-artifact v2 composite
.github/workflows/linting_comment.yml actions
  • dawidd6/action-download-artifact v2 composite
  • marocchino/sticky-pull-request-comment v2 composite
modules/nf-core/bcftools/sort/meta.yml cpan
modules/nf-core/custom/dumpsoftwareversions/meta.yml cpan
modules/nf-core/fastqc/meta.yml cpan
modules/nf-core/multiqc/meta.yml cpan
modules/nf-core/nanolyse/meta.yml cpan
modules/nf-core/nanoplot/meta.yml cpan
modules/nf-core/samtools/faidx/meta.yml cpan
modules/nf-core/samtools/flagstat/meta.yml cpan
modules/nf-core/samtools/idxstats/meta.yml cpan
modules/nf-core/samtools/index/meta.yml cpan
modules/nf-core/samtools/sort/meta.yml cpan
modules/nf-core/samtools/stats/meta.yml cpan
modules/nf-core/stringtie/merge/meta.yml cpan
modules/nf-core/tabix/bgzip/meta.yml cpan
modules/nf-core/tabix/bgziptabix/meta.yml cpan
modules/nf-core/tabix/tabix/meta.yml cpan
modules/nf-core/untar/meta.yml cpan
pyproject.toml pypi