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sammyseq

Pipeline for Sequential Analysis of MacroMolecules accessibilitY sequencing (SAMMY-seq) data, to analyze chromatin state.

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

Science Score: 67.0%

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    Found 14 DOI reference(s) in README
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Keywords

3d-genome bioinformatics chromatin dna epigenetics epigenome epigenomics genome genomics next-generation-sequencing nextflow nf-core ngs pipeline sequencing workflow
Last synced: 6 months ago · JSON representation ·

Repository

Pipeline for Sequential Analysis of MacroMolecules accessibilitY sequencing (SAMMY-seq) data, to analyze chromatin state.

Basic Info
  • Host: GitHub
  • Owner: nf-core
  • License: mit
  • Language: Nextflow
  • Default Branch: dev
  • Homepage: https://nf-co.re/sammyseq
  • Size: 5.25 MB
Statistics
  • Stars: 5
  • Watchers: 171
  • Forks: 15
  • Open Issues: 7
  • Releases: 0
Topics
3d-genome bioinformatics chromatin dna epigenetics epigenome epigenomics genome genomics next-generation-sequencing nextflow nf-core ngs pipeline sequencing workflow
Created over 3 years ago · Last pushed 7 months ago
Metadata Files
Readme Changelog Contributing License Code of conduct Citation

README.md

nf-core/sammyseq

GitHub Actions CI Status GitHub Actions Linting StatusAWS CICite with Zenodo nf-test

Nextflow nf-core template version run with conda run with docker run with singularity Launch on Seqera Platform

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Introduction

nf-core/sammyseq is a bioinformatics pipeline for the analysis of Sequential Analysis of MacroMolecules accessibilitY sequencing (SAMMY-seq) data, a cheap and effective methodology to analyze chromatin state as described in:

Lucini F, Petrini C, Salviato E, Pal K, Rosti V, Gorini F, Santarelli P, Quadri R, Lembo G, Graziano G, Di Patrizio Soldateschi E, Tagliaferri I, Pinatel E, Sebestyén E, Rotta L, Gentile F, Vaira V, Lanzuolo C, Ferrari F. Biochemical properties of chromatin domains define genome compartmentalization. Nucleic Acids Research, Volume 52, Issue 12, 8 July 2024, Page e54 doi pubmed

Sebestyén, E., Marullo, F., Lucini, F. et al. SAMMY-seq reveals early alteration of heterochromatin and deregulation of bivalent genes in Hutchinson-Gilford Progeria Syndrome. Nat Commun 11, 6274 (2020) doi pubmed

[!WARNING] Please note that this pipeline is under active development and has not been released yet.

Here is an outline of the analysis steps:

  1. Read QC (FastQC)
  2. Trim reads to remove adapter sequences and low quality ends (Trim Galore! or Trimmomatic)
  3. Align on a reference genome (BWA or Bowtie 2)
  4. Mark duplicate reads (picard Markduplicates)
  5. Filter reads and generate alignment statistics (samtools)
  6. Create single track profiles in bigwig format (deeptools)
  7. (Optionally) Generate pairwise comparison tracks in bigwig format if provided a list of the desired sample pairs ([spp])
  8. Generate an analysis report by collecting all generated QC and statistics (MultiQC)

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.

First, prepare a samplesheet with your input data that looks as follows:

samplesheet.csv:

csv sample,fastq_1,fastq_2,experimentalID,fraction,sample_group CTRL004_S2,/home/sammy/test_data/CTRL004_S2_chr22only.fq.gz,,CTRL004,S2,CTRL CTRL004_S3,/home/sammy/test_data/CTRL004_S3_chr22only.fq.gz,,CTRL004,S3,CTRL CTRL004_S4,/home/sammy/test_data/CTRL004_S4_chr22only.fq.gz,,CTRL004,S4,CTRL

Each row represents a fastq file (single-end) or a pair of fastq files (paired end), experimentalID represents the biological specimen of interest and sample the library produced for each fraction, it usually is a unique combination of experimentalID and fraction. The sample_group field is used to group samples that belong to the same biological condition.

Now, you can run the pipeline using:

bash nextflow run nf-core/sammyseq \ -profile <docker/singularity/.../institute> \ --fasta reference_genome.fa \ --input samplesheet.csv \ --outdir <OUTDIR>

or

bash nextflow run nf-core/sammyseq \ -profile <docker/singularity/.../institute> \ --fasta reference_genome.fa \ --input samplesheet.csv \ --outdir <OUTDIR> \ --comparison S2SvsS3

[!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.

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

Pipeline output

For more details about the output files and reports, please refer to the output documentation.

Credits

The SAMMY-seq data analysis procedure was originally developed by the laboratory of Francesco Ferrari (IFOM-ETS, Milan; IGM-CNR, Pavia) in collaboration with the laboratory of Chiara Lanzuolo (INGM, Milan; ITB-CNR, Segrate). The orginal pipeline backbone was mainly the result of work by Cristiano Petrini (IFOM) and Endre Sebestyén (IFOM), with significant contributions by Ilario Tagliaferri (IFOM), Giovanni Lembo (IFOM) and Emanuele Di Patrizio Soldateschi (INGM). The project also benefited from the collaboration and input by Eva Maria Pinatel (ITB-CNR). The product of this effort resulted in a first pipeline implemented in bash and adapted to work on Sun Grid Engine (SGE) scheduler.

The nf-core pipeline (nf-core/sammyseq) is being implemented by Lucio Di Filippo (ISASI-CNR, Pozzuoli; IBBTEC, Santander), Ugo Maria Iannacchero (ITB-CNR) and Margherita Mutarelli (ISASI-CNR).

Many thanks to others who have helped out and contributed along the way too, including (but not limited to): Phil Ewels, Maxime Ulysse Garcia, Friederike Hanssen, Matthias Hörtenhuber, Marinicla Pascale, Júlia Mir-Pedrol and Marcel Ribeiro-Dantas.

Acknowledgements

The development of this pipeline was made possible thanks to the projects Progetti@CNR Myo-CoV-2 B93C20046330005, AFM Téléthon EDMD-GenomeSCAN B53C22009260007 and PIR01_00011 I.Bi.S.Co. Infrastruttura per Big data e Scientific COmputing (PON 2014-2020).

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 #sammyseq channel (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/sammyseq: 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.

- [Bowtie 2](https://bowtie-bio.sourceforge.net/bowtie2)

  > Langmead B, Salzberg SL. Fast gapped-read alignment with Bowtie 2. Nat Methods. 2012 Mar 4;9(4):357-9. doi: 10.1038/nmeth.1923. PMID: 22388286; PMCID: PMC3322381.

- [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].

- [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.

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

- [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.

- [Trim Galore!](https://github.com/FelixKrueger/TrimGalore)

- [Trimmomatic](https://pubmed.ncbi.nlm.nih.gov/24695404/)

  > Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014 Aug 1;30(15):2114-20. doi: 10.1093/bioinformatics/btu170. Epub 2014 Apr 1. PMID: 24695404; PMCID: PMC4103590.

## 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.

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

  > Dowle M, Srinivasan A (2023). data.table: Extension of 'data.frame'. https://r-datatable.com, https://Rdatatable.gitlab.io/data.table, https://github.com/Rdatatable/data.table.

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

  > Eddelbuettel, D., & Francois, R. (2011). Rcpp: Seamless R and C++ Integration. Journal of Statistical Software, 40(8), 1–18. https://doi.org/10.18637/jss.v040.i08

- [rtracklayer](https://bioconductor.org/packages/rtracklayer)

  > Lawrence M, Gentleman R, Carey V (2009). “rtracklayer: an R package for interfacing with genome browsers.” Bioinformatics, 25, 1841-1842. doi:10.1093/bioinformatics/btp328, http://bioinformatics.oxfordjournals.org/content/25/14/1841.abstract.

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

  > Kharchenko PK, Tolstorukov MY, Park PJ "Design and analysis of ChIP-seq experiments for DNA-binding proteins" Nat. Biotech. doi:10.1038/nbt.1508

## 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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