chipseq

ChIP-seq peak-calling, QC and differential analysis pipeline.

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

Science Score: 77.0%

This score indicates how likely this project is to be science-related based on various indicators:

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CITATION.cff file
Found CITATION.cff file
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codemeta.json file
Found codemeta.json file
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DOI references
Found 10 DOI reference(s) in README
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Links to: pubmed.ncbi, ncbi.nlm.nih.gov
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1 of 18 committers (5.6%) from academic institutions
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Low similarity (8.8%) to scientific vocabulary

Keywords

chip chip-seq chromatin-immunoprecipitation macs2 nextflow nf-core peak-calling pipeline workflow

Keywords from Contributors

atac-seq chromatin-accessibiity 16s 18s amplicon-sequencing edna illumina iontorrent its metabarcoding

Last synced: 6 months ago · JSON representation ·

Repository

ChIP-seq peak-calling, QC and differential analysis pipeline.

Basic Info

Host: GitHub
Owner: nf-core
License: mit
Language: Nextflow
Default Branch: master
Homepage: https://nf-co.re/chipseq
Size: 16 MB

Statistics

Stars: 219
Watchers: 162
Forks: 158
Open Issues: 34
Releases: 7

Topics

chip chip-seq chromatin-immunoprecipitation macs2 nextflow nf-core peak-calling pipeline workflow

Created almost 8 years ago · Last pushed 6 months ago

Metadata Files

Readme Changelog Contributing License Code of conduct Citation

Introduction

nfcore/chipseq is a bioinformatics analysis pipeline used for Chromatin ImmunoPrecipitation sequencing (ChIP-seq) data.

On release, automated continuous integration tests run the pipeline on a full-sized dataset on the AWS cloud infrastructure. The dataset consists of FoxA1 (transcription factor) and EZH2 (histone,mark) IP experiments from Franco et al. 2015 (GEO: GSE59530, PMID: 25752574) and Popovic et al. 2014 (GEO: GSE57632, PMID: 25188243), respectively. 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 running the full-sized tests can be viewed on the nf-core website.

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!

Online videos

A short talk about the history, current status and functionality on offer in this pipeline was given by Jose Espinosa-Carrasco (@joseespinosa) on 26th July 2022 as part of the nf-core/bytesize series.

You can find numerous talks on the nf-core events page from various topics including writing pipelines/modules in Nextflow DSL2, using nf-core tooling, running nf-core pipelines as well as more generic content like contributing to Github. Please check them out!

Pipeline summary

nf-core/chipseq metro map

Raw read QC (FastQC)
Adapter trimming (Trim Galore!)
Choice of multiple aligners 1.(BWA) 2.(Chromap) 3.(Bowtie2) 4.(STAR)
Mark duplicates (picard)
Merge alignments from multiple libraries of the same sample (picard)
1. Re-mark duplicates (picard)
2. Filtering to remove:
  - reads mapping to blacklisted regions (SAMtools, BEDTools)
  - reads that are marked as duplicates (SAMtools)
  - reads that are not marked as primary alignments (SAMtools)
  - reads that are unmapped (SAMtools)
  - reads that map to multiple locations (SAMtools)
  - reads containing > 4 mismatches (BAMTools)
  - reads that have an insert size > 2kb (BAMTools; paired-end only)
  - reads that map to different chromosomes (Pysam; paired-end only)
  - reads that arent in FR orientation (Pysam; paired-end only)
  - reads where only one read of the pair fails the above criteria (Pysam; paired-end only)
3. Alignment-level QC and estimation of library complexity (picard, Preseq)
4. Create normalised bigWig files scaled to 1 million mapped reads (BEDTools, bedGraphToBigWig)
5. Generate gene-body meta-profile from bigWig files (deepTools)
6. Calculate genome-wide IP enrichment relative to control (deepTools)
7. Calculate strand cross-correlation peak and ChIP-seq quality measures including NSC and RSC (phantompeakqualtools)
8. Call broad/narrow peaks (MACS3)
9. Annotate peaks relative to gene features (HOMER)
10. Create consensus peakset across all samples and create tabular file to aid in the filtering of the data (BEDTools)
11. Count reads in consensus peaks (featureCounts)
12. PCA and clustering (R, DESeq2)
Create IGV session file containing bigWig tracks, peaks and differential sites for data visualisation (IGV).
Present QC for raw read, alignment, peak-calling and differential binding results (MultiQC, R)

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.

To run on your data, prepare a tab-separated samplesheet with your input data. Please follow the documentation on samplesheets for more details. An example samplesheet for running the pipeline looks as follows:

csv title="samplesheet.csv" sample,fastq_1,fastq_2,replicate,antibody,control,control_replicate WT_BCATENIN_IP,BLA203A1_S27_L006_R1_001.fastq.gz,,1,BCATENIN,WT_INPUT,1 WT_BCATENIN_IP,BLA203A25_S16_L001_R1_001.fastq.gz,,2,BCATENIN,WT_INPUT,2 WT_BCATENIN_IP,BLA203A25_S16_L002_R1_001.fastq.gz,,2,BCATENIN,WT_INPUT,2 WT_BCATENIN_IP,BLA203A25_S16_L003_R1_001.fastq.gz,,2,BCATENIN,WT_INPUT,2 WT_BCATENIN_IP,BLA203A49_S40_L001_R1_001.fastq.gz,,3,BCATENIN,WT_INPUT,3 WT_INPUT,BLA203A6_S32_L006_R1_001.fastq.gz,,1,,, WT_INPUT,BLA203A30_S21_L001_R1_001.fastq.gz,,2,,, WT_INPUT,BLA203A30_S21_L002_R1_001.fastq.gz,,2,,, WT_INPUT,BLA203A31_S21_L003_R1_001.fastq.gz,,3,,,

Now, you can run the pipeline using:

bash nextflow run nf-core/chipseq --input samplesheet.csv --outdir <OUTDIR> --genome GRCh37 -profile <docker/singularity/podman/shifter/charliecloud/conda/institute>

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

[!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 the docs here.

For more details and further functionality, please refer to the usage documentation and the parameter documentation.

Pipeline output

To see the results of an example test run with a full size dataset refer to the results tab on the nf-core website pipeline page. For more details about the output files and reports, please refer to the output documentation.

Credits

These scripts were originally written by Chuan Wang (@chuan-wang) and Phil Ewels (@ewels) for use at the National Genomics Infrastructure at SciLifeLab in Stockholm, Sweden. The pipeline was re-implemented by Harshil Patel (@drpatelh) from Seqera Labs, Spain and converted to Nextflow DSL2 by Jose Espinosa-Carrasco (@JoseEspinosa) from The Comparative Bioinformatics Group at The Centre for Genomic Regulation, Spain.

The pipeline workflow diagram was designed by Sarah Guinchard (@G-Sarah).

Many thanks to others who have helped out and contributed along the way too, including (but not limited to): @apeltzer, @bc2zb, @bjlang, @crickbabs, @drejom, @houghtos, @KevinMenden, @mashehu, @pditommaso, @Rotholandus, @sofiahaglund, @tiagochst and @winni2k.

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

Citations

If you use nf-core/chipseq for your analysis, please cite it using the following doi: 10.5281/zenodo.3240506

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

Website: http://nf-co.re
Twitter: nf_core
Repositories: 84
Profile: https://github.com/nf-core

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

Citation (CITATIONS.md)

# nf-core/chipseq: 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

- [BWA](https://www.ncbi.nlm.nih.gov/pubmed/19451168/)

  > Li H, Durbin R. Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics. 2009 Jul 15;25(14):1754-60. doi: 10.1093/bioinformatics/btp324. Epub 2009 May 18. PubMed PMID: 19451168; PubMed Central PMCID: PMC2705234.

- [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.

- [BamTools](https://www.ncbi.nlm.nih.gov/pubmed/21493652/)

  > Barnett DW, Garrison EK, Quinlan AR, Strömberg MP, Marth GT. BamTools: a C++ API and toolkit for analyzing and managing BAM files. Bioinformatics. 2011 Jun 15;27(12):1691-2. doi: 10.1093/bioinformatics/btr174. Epub 2011 Apr 14. PubMed PMID: 21493652; PubMed Central PMCID: PMC3106182.

- [Bowtie2](https:/dx.doi.org/10.1038/nmeth.1923)

  > Langmead, B. and Salzberg, S. L. 2012 Fast gapped-read alignment with Bowtie 2. Nature methods, 9(4), p. 357–359. doi: 10.1038/nmeth.1923.

- [Chromap](https://doi.org/10.1038/s41467-021-26865-w)

  > Zhang H, Song L, Wang X, Cheng H, Wang C, Meyer CA, Liu T, Tang M, Aluru S, Yue F, Liu XS and Li H. Fast alignment and preprocessing of chromatin profiles with Chromap. Nature communications. 2021, 12(1), 1-6. doi: 10.1038/s41467-021-26865-w

- [deepTools](https://www.ncbi.nlm.nih.gov/pubmed/27079975/)

  > Ramírez F, Ryan DP, Grüning B, Bhardwaj V, Kilpert F, Richter AS, Heyne S, Dündar F, Manke T. deepTools2: a next generation web server for deep-sequencing data analysis. Nucleic Acids Res. 2016 Jul 8;44(W1):W160-5. doi: 10.1093/nar/gkw257. Epub 2016 Apr 13. PubMed PMID: 27079975; PubMed Central PMCID: PMC4987876.

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

> Andrews, S. (2010). FastQC: A Quality Control Tool for High Throughput Sequence Data [Online]. Available online https://www.bioinformatics.babraham.ac.uk/projects/fastqc/.

- [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.

- [HOMER](https://www.ncbi.nlm.nih.gov/pubmed/20513432/)

  > Heinz S, Benner C, Spann N, Bertolino E, Lin YC, Laslo P, Cheng JX, Murre C, Singh H, Glass CK. Simple combinations of lineage-determining transcription factors prime cis-regulatory elements required for macrophage and B cell identities. Mol Cell. 2010 May 28;38(4):576-89. doi: 10.1016/j.molcel.2010.05.004. PubMed PMID: 20513432; PubMed Central PMCID: PMC2898526.

- [MACS3](https://www.ncbi.nlm.nih.gov/pubmed/18798982/)

  > Zhang Y, Liu T, Meyer CA, Eeckhoute J, Johnson DS, Bernstein BE, Nusbaum C, Myers RM, Brown M, Li W, Liu XS. Model-based analysis of ChIP-Seq (MACS). Genome Biol. 2008;9(9):R137. doi: 10.1186/gb-2008-9-9-r137. Epub 2008 Sep 17. PubMed PMID: 18798982; PubMed Central PMCID: PMC2592715.

- [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.

- [phantompeakqualtools](https://www.ncbi.nlm.nih.gov/pubmed/22955991/)

  > Landt SG, Marinov GK, Kundaje A, Kheradpour P, Pauli F, Batzoglou S, Bernstein BE, Bickel P, Brown JB, Cayting P, Chen Y, DeSalvo G, Epstein C, Fisher-Aylor KI, Euskirchen G, Gerstein M, Gertz J, Hartemink AJ, Hoffman MM, Iyer VR, Jung YL, Karmakar S, Kellis M, Kharchenko PV, Li Q, Liu T, Liu XS, Ma L, Milosavljevic A, Myers RM, Park PJ, Pazin MJ, Perry MD, Raha D, Reddy TE, Rozowsky J, Shoresh N, Sidow A, Slattery M, Stamatoyannopoulos JA, Tolstorukov MY, White KP, Xi S, Farnham PJ, Lieb JD, Wold BJ, Snyder M. ChIP-seq guidelines and practices of the ENCODE and modENCODE consortia. Genome Res. 2012 Sep;22(9):1813-31. doi: 10.1101/gr.136184.111. PubMed PMID: 22955991; PubMed Central PMCID: PMC3431496.

- [picard-tools](http://broadinstitute.github.io/picard)

- [preseq](https://www.ncbi.nlm.nih.gov/pubmed/23435259/)

  > Daley T, Smith AD. Predicting the molecular complexity of sequencing libraries. Nat Methods. 2013 Apr;10(4):325-7. doi: 10.1038/nmeth.2375. Epub 2013 Feb 24. PubMed PMID: 23435259; PubMed Central PMCID: PMC3612374.

- [pysam](https://github.com/pysam-developers/pysam)

- [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.

- [STAR](https://pubmed.ncbi.nlm.nih.gov/23104886/)

  > Dobin A, Davis CA, Schlesinger F, Drenkow J, Zaleski C, Jha S, Batut P, Chaisson M, Gingeras TR. STAR: ultrafast universal RNA-seq aligner Bioinformatics. 2013 Jan 1;29(1):15-21. doi: 10.1093/bioinformatics/bts635. Epub 2012 Oct 25. PubMed PMID: 23104886; PubMed Central PMCID: PMC3530905.

- [Trim Galore!](https://www.bioinformatics.babraham.ac.uk/projects/trim_galore/)

- [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.

## 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.

- [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.

- [UpSetR](https://CRAN.R-project.org/package=UpSetR)

  > Nils Gehlenborg (2017). UpSetR: A More Scalable Alternative to Venn and Euler Diagrams for Visualizing Intersecting Sets.

- [ggplot2](https://cran.r-project.org/web/packages/ggplot2/index.html)

  > H. Wickham. ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York, 2016.

- [reshape2](http://www.jstatsoft.org/v21/i12/)

  > Hadley Wickham (2007). Reshaping Data with the reshape Package. Journal of Statistical Software, 21(12), 1-20.

- [scales](https://CRAN.R-project.org/package=scales)

  > Hadley Wickham (2018). scales: Scale Functions for Visualization.

- [pheatmap](https://CRAN.R-project.org/package=pheatmap)

  > Raivo Kolde (2018). pheatmap: Pretty Heatmaps.

- [RColorBrewer](https://CRAN.R-project.org/package=RColorBrewer)

  > Erich Neuwirth (2014). RColorBrewer: ColorBrewer Palettes.

- [optparse](https://CRAN.R-project.org/package=optparse)

  > Trevor L Davis (2018). optparse: Command Line Option Parser.

## 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

Issues event: 20
Watch event: 31
Delete event: 9
Issue comment event: 46
Push event: 29
Pull request review comment event: 25
Pull request review event: 28
Pull request event: 37
Fork event: 14
Create event: 14

Last Year

Issues event: 20
Watch event: 31
Delete event: 9
Issue comment event: 46
Push event: 29
Pull request review comment event: 25
Pull request review event: 28
Pull request event: 37
Fork event: 14
Create event: 14

Committers

Last synced: over 2 years ago

All Time

Total Commits: 1,288
Total Committers: 18
Avg Commits per committer: 71.556
Development Distribution Score (DDS): 0.556

Past Year

Commits: 134
Committers: 4
Avg Commits per committer: 33.5
Development Distribution Score (DDS): 0.261

Top Committers

Name	Email	Commits
drpatelh	d**l@g**m	572
JoseEspinosa	k**u@g**m	309
Chuan Wang	c**g@s**e	143
Phil Ewels	p**s@s**e	106
Alexander Peltzer	a**r@u**e	56
Harshil Patel	d**h@g**m	47
nf-core-bot	c**e@n**e	19
Tiago Chedraoui Silva	t**t@g**m	15
Harshil Patel	d**h@u**m	8
Drew Behrens	d**h@g**m	3
MaxUlysse	m**a@g**m	3
Rotholandus	l**e@u**l	1
Sofia Haglund	s**d@s**e	1
Warren W. Kretzschmar	w**h@g**m	1
mashehu	m**u@u**m	1
kevinmenden	k**n@t**e	1
runner	r**r@f**0	1
matthiasho	m**r@k**e	1

Committer Domains (Top 20 + Academic)

scilifelab.se: 3 ki.se: 1 t-online.de: 1 uc.cl: 1 nf-co.re: 1 uni-tuebingen.de: 1

Issues and Pull Requests

Last synced: 6 months ago

All Time

Total issues: 85
Total pull requests: 127
Average time to close issues: 8 months
Average time to close pull requests: 17 days
Total issue authors: 66
Total pull request authors: 19
Average comments per issue: 2.35
Average comments per pull request: 0.78
Merged pull requests: 79
Bot issues: 0
Bot pull requests: 0

Past Year

Issues: 20
Pull requests: 33
Average time to close issues: 4 days
Average time to close pull requests: 4 days
Issue authors: 15
Pull request authors: 9
Average comments per issue: 0.25
Average comments per pull request: 0.55
Merged pull requests: 11
Bot issues: 0
Bot pull requests: 0

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Top Authors

Issue Authors

JoseEspinosa (14)
IStevant (2)
ftabaro (2)
aubinthomas (2)
CLAIRE-cuhk (2)
FelixKrueger (2)
Sungryong-Oh (2)
alextruong (1)
dannyjwan (1)
StevenWingett (1)
aghr (1)
Emiller88 (1)
amibe1 (1)
BalajiVenkadakrishnan (1)
drpatelh (1)

Pull Request Authors

JoseEspinosa (64)
nf-core-bot (32)
drpatelh (5)
bjlang (5)
Lehmann-Fabian (3)
G-Sarah (2)
edmundmiller (2)
gppbioinfo (2)
ftabaro (2)
ftamiro (1)
tavareshugo (1)
mashehu (1)
LeonHafner (1)
smoe (1)
samuelruizperez (1)

Top Labels

Issue Labels

bug (30) enhancement (25) question (7) docs (3) feature-request (2) improve-behaviour (2) duplicate (2) help wanted (1) DSL2 v2.0 (1) wontfix (1) WIP (1)

Pull Request Labels

Dependencies

.github/workflows/fix-linting.yml actions

actions/checkout v3 composite
actions/setup-node v2 composite

.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
nf-core/setup-nextflow v1 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
mshick/add-pr-comment v1 composite
nf-core/setup-nextflow v1 composite
psf/black stable composite

.github/workflows/linting_comment.yml actions

dawidd6/action-download-artifact v2 composite
marocchino/sticky-pull-request-comment v2 composite

modules/nf-core/modules/bowtie2/align/meta.yml cpan

modules/nf-core/modules/bowtie2/build/meta.yml cpan

modules/nf-core/modules/bwa/index/meta.yml cpan

modules/nf-core/modules/bwa/mem/meta.yml cpan

modules/nf-core/modules/chromap/chromap/meta.yml cpan

modules/nf-core/modules/chromap/index/meta.yml cpan

modules/nf-core/modules/custom/dumpsoftwareversions/meta.yml cpan

modules/nf-core/modules/custom/getchromsizes/meta.yml cpan

modules/nf-core/modules/deeptools/computematrix/meta.yml cpan

modules/nf-core/modules/deeptools/plotfingerprint/meta.yml cpan

modules/nf-core/modules/deeptools/plotheatmap/meta.yml cpan

modules/nf-core/modules/deeptools/plotprofile/meta.yml cpan

modules/nf-core/modules/fastqc/meta.yml cpan

modules/nf-core/modules/gffread/meta.yml cpan

modules/nf-core/modules/gunzip/meta.yml cpan

modules/nf-core/modules/homer/annotatepeaks/meta.yml cpan

modules/nf-core/modules/khmer/uniquekmers/meta.yml cpan

modules/nf-core/modules/macs2/callpeak/meta.yml cpan

modules/nf-core/modules/phantompeakqualtools/meta.yml cpan

modules/nf-core/modules/picard/collectmultiplemetrics/meta.yml cpan

modules/nf-core/modules/picard/markduplicates/meta.yml cpan

modules/nf-core/modules/picard/mergesamfiles/meta.yml cpan

modules/nf-core/modules/preseq/lcextrap/meta.yml cpan

modules/nf-core/modules/samtools/flagstat/meta.yml cpan

modules/nf-core/modules/samtools/idxstats/meta.yml cpan

modules/nf-core/modules/samtools/index/meta.yml cpan

modules/nf-core/modules/samtools/sort/meta.yml cpan

modules/nf-core/modules/samtools/stats/meta.yml cpan

modules/nf-core/modules/subread/featurecounts/meta.yml cpan

modules/nf-core/modules/trimgalore/meta.yml cpan

modules/nf-core/modules/ucsc/bedgraphtobigwig/meta.yml cpan

modules/nf-core/modules/untar/meta.yml cpan

pyproject.toml pypi

chipseq

Science Score: 77.0%

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