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mnaseseq

MNase-seq analysis pipeline using BWA and DANPOS2.

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

Science Score: 44.0%

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Keywords

mnase-seq nextflow nf-core nucleosome nucleosome-maps nucleosome-positioning pipeline workflow

Keywords from Contributors

metagenomics rna chip chip-seq chromatin-immunoprecipitation illumina macs2 peak-calling assembly long-read-sequencing
Last synced: 6 months ago · JSON representation ·

Repository

MNase-seq analysis pipeline using BWA and DANPOS2.

Basic Info
  • Host: GitHub
  • Owner: nf-core
  • License: mit
  • Language: Nextflow
  • Default Branch: master
  • Homepage: https://nf-co.re/mnaseseq
  • Size: 4.53 MB
Statistics
  • Stars: 10
  • Watchers: 130
  • Forks: 8
  • Open Issues: 6
  • Releases: 1
Topics
mnase-seq nextflow nf-core nucleosome nucleosome-maps nucleosome-positioning pipeline workflow
Created over 6 years ago · Last pushed almost 2 years ago
Metadata Files
Readme Changelog Contributing License Code of conduct Citation

README.md

nf-core/mnaseseq

GitHub Actions CI Status GitHub Actions Linting Status Nextflow

install with bioconda Docker Cite with Zenodo

Introduction

nfcore/mnaseseq is a bioinformatics analysis pipeline used for DNA sequencing data obtained via micrococcal nuclease digestion.

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.

Pipeline summary

  1. Raw read QC (FastQC)
  2. Adapter trimming (Trim Galore!)
  3. Alignment (BWA)
  4. Mark duplicates (picard)
  5. 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 arent marked as primary alignments (SAMtools)
      • reads that are unmapped (SAMtools)
      • reads that map to multiple locations (SAMtools)
      • reads containing > 4 mismatches (BAMTools)
      • reads that are soft-clipped (BAMTools)
      • reads that have an insert size within specified range (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. Calculate genome-wide coverage assessment (deepTools)
    6. Call nucleosome positions and generate smoothed, normalised coverage bigWig files that can be used to generate occupancy profile plots between samples across features of interest (DANPOS2)
    7. Generate gene-body meta-profile from DANPOS2 smoothed bigWig files (deepTools)
  6. Merge filtered alignments across replicates (picard)
    1. Re-mark duplicates (picard)
    2. Remove duplicate reads (SAMtools)
    3. Create normalised bigWig files scaled to 1 million mapped reads (BEDTools, wigToBigWig)
    4. Call nucleosome positions and generate smoothed, normalised coverage bigWig files that can be used to generate occupancy profile plots between samples across features of interest (DANPOS2)
    5. Generate gene-body meta-profile from DANPOS2 smoothed bigWig files (deepTools)
  7. Create IGV session file containing bigWig tracks for data visualisation (IGV).
  8. Present QC for raw read and alignment results (MultiQC)

Quick Start

i. Install nextflow

ii. Install either Docker or Singularity for full pipeline reproducibility (please only use Conda as a last resort; see docs)

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

bash nextflow run nf-core/mnaseseq -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.

iv. Start running your own analysis!

bash nextflow run nf-core/mnaseseq -profile <docker/singularity/conda/institute> --input design.csv --genome GRCh37

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

Documentation

The nf-core/mnaseseq pipeline comes with documentation about the pipeline, found in the docs/ directory:

  1. Installation
  2. Pipeline configuration
  3. Running the pipeline
  4. Output and how to interpret the results
  5. Troubleshooting

Credits

The pipeline was originally written by The Bioinformatics & Biostatistics Group for use at The Francis Crick Institute, London.

The pipeline was developed by Harshil Patel.

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

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).

Citation

If you use nf-core/mnaseseq for your analysis, please cite it using the following doi: 10.5281/zenodo.6581372.

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/atacseq: 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.

* [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.

* [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.

* [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.

* [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.

* [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.

* [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.

* [DANPOS2](https://www.ncbi.nlm.nih.gov/pubmed/26301496/)
  > Chen K, Chen Z, Wu D, Zhang L, Lin X, Su J, Rodriguez B, Xi Y, Xia Z, Chen X, Shi X, Wang Q, Li W. Broad H3K4me3 is associated with increased transcription elongation and enhancer activity at tumor-suppressor genes. Nat Genet. 2015 Oct;47(10):1149-57. doi: 10.1038/ng.3385. Epub 2015 Aug 24. PubMed PMID: 26301496; PubMed Central PMCID: PMC4780747.

* [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.

* [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.

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

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

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

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

## Software packaging/containerisation tools

* [Bioconda](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. 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.

* [Anaconda](https://anaconda.com)
  > Anaconda Software Distribution. Computer software. Vers. 2-2.4.0. Anaconda, Nov. 2016. Web.

* [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.

* [Docker](https://www.docker.com/)

GitHub Events

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  • Issues event: 1
  • Watch event: 2
  • Fork event: 2
Last Year
  • Issues event: 1
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  • Fork event: 2

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Last synced: over 2 years ago

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  • Total Commits: 145
  • Total Committers: 4
  • Avg Commits per committer: 36.25
  • Development Distribution Score (DDS): 0.069
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  • Avg Commits per committer: 0.0
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Last synced: about 2 years ago

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  • Total issues: 4
  • Total pull requests: 38
  • Average time to close issues: N/A
  • Average time to close pull requests: 2 months
  • Total issue authors: 4
  • Total pull request authors: 6
  • Average comments per issue: 0.5
  • Average comments per pull request: 0.66
  • Merged pull requests: 14
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
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  • Pull requests: 5
  • Average time to close issues: N/A
  • Average time to close pull requests: 3 months
  • Issue authors: 0
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  • Average comments per issue: 0
  • Average comments per pull request: 0.8
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Dependencies

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.github/workflows/ci.yml actions
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.github/workflows/linting.yml actions
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  • actions/checkout v1 composite
  • actions/setup-node v1 composite
  • actions/setup-python v1 composite
Dockerfile docker
  • nfcore/base 1.9 build
environment.yml pypi