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 Res. 2024 Jul 8;52(12):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

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

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Here is an outline of the analysis steps:

1. Read QC (FastQC)
2. Trim reads to remove adapter sequences and low quality ends (Trimmomatic)
3. Align on a reference genome (BWA)
4. Remove duplicate reads (picard Markduplicates)
5. 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:

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

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.

Now, you can run the pipeline using:

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

or

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

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

nf-core/sammyseq was written by Lucio Di Filippo and Margherita Mutarelli and was based on the original pipeline developed in-house by SAMMY-seq creators.

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.