oncoanalyser-cloudos

https://github.com/scwatts/oncoanalyser-cloudos

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Host: GitHub
Owner: scwatts
License: mit
Language: Nextflow
Default Branch: dev
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Readme Changelog Contributing License Code of conduct Citation

Introduction

nf-core/oncoanalyser is a Nextflow implementation of the comprehensive cancer DNA/RNA analysis and reporting workflow from the Hartwig Medical Foundation (HMF). The workflow starts from FASTQ or BAM and calls genomic variants, analyses transcript data, infers important biomarkers and features (e.g. TMB, HRD, mutational signatures, HLA alleles, oncoviral content, tissue of origin, etc), annotates and interprets results in the clinical context, and more.

Both the HMF WGS/WTS workflow and targeted sequencing workflow are available in oncoanalyser. The targeted sequencing workflow has built-in support for the TSO500 panel and can also run custom panels with externally-generated normalisation data.

The key analysis results for each sample are summarised and presented in an ORANGE report (summary page excerpt shown below from [COLO829wgts.orangereport.pdf](https://pub-29f2e5b2b7384811bdbbcba44f8b5083.r2.dev/oncoanalyser/other/examplereport/COLO829wgts.orangereport.pdf)_):

For detailed information on each component of the HMF workflow, please refer to hartwigmedical/hmftools.

Pipeline summary

The following processes and tools can be run with oncoanalyser:

Simple DNA/RNA alignment (bwa-mem2, STAR)
Post-alignment processing (MarkDups, Picard MarkDuplicates)
SNV, MNV, and INDEL calling (SAGE, PAVE)
CNV calling (AMBER, COBALT, PURPLE)
SV calling (SvPrep, GRIDSS, GRIPSS)
SV event interpretation (LINX)
Transcript analysis (Isofox)
Oncoviral detection (VIRUSBreakend, Virus Interpreter)
HLA calling (LILAC)
HRD status prediction (CHORD)
Mutational signature fitting (Sigs)
Tissue of origin prediction (CUPPA)
Report generation (ORANGE, linxreport)

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.

Create a samplesheet with your inputs (WGS/WTS FASTQs in this example):

csv group_id,subject_id,sample_id,sample_type,sequence_type,filetype,info,filepath P1__wgts,P1,SA,normal,dna,fastq,library_id:SA_library;lane:001,/path/to/SA.normal.dna.wgs.001.R1.fastq.gz;/path/to/SA.normal.dna.wgs.001.R2.fastq.gz P1__wgts,P1,SB,tumor,dna,fastq,library_id:SB_library;lane:001,/path/to/SB.tumor.dna.wgs.001.R1.fastq.gz;/path/to/SB.tumor.dna.wgs.001.R2.fastq.gz P1__wgts,P1,SC,tumor,rna,fastq,library_id:SC_library;lane:001,/path/to/SC.tumor.rna.wts.001.R1.fastq.gz;/path/to/SC.tumor.rna.wts.001.R2.fastq.gz

Launch oncoanalyser:

bash nextflow run nf-core/oncoanalyser \ -profile docker \ -revision 1.0.0 \ --mode wgts \ --genome GRCh38_hmf \ --input samplesheet.csv \ --outdir output/

[!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

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.

Version information

Extended support

As oncoanalyser is used in clinical settings and subject to accreditation standards in some instances, there is a need for long-term stability and reliability for feature releases in order to meet operational requirements. This is accomplished through long-term support of several nominated feature releases, which all receive bug fixes and security fixes during the period of extended support.

Each release that is given extended support is allocated a separate long-lived git branch with the 'stable' prefix, e.g. stable/1.2.x, stable/1.5.x. Feature development otherwise occurs on the dev branch with stable releases pushed to master.

Versions nominated to have current long-term support:

TBD

Release parity

Versioning between oncoanalyser and hmftools naturally differ, however it is often necessary to relate the functional equivalence of these two pieces of software. The functional/feature parity with regards to version releases are detailed in the below table.

| oncoanalyser | hmftools | | ------------------- | -------- | | 0.1.0 through 0.2.7 | 5.33 | | 0.3.0 through 1.0.0 | 5.34 |

Known issues

There are currently no known issues.

Credits

The oncoanalyser pipeline was written by Stephen Watts while in the Genomics Platform Group at the University of Melbourne Centre for Cancer Research.

We thank the following organisations and people for their extensive assistance in the development of this pipeline, listed in alphabetical order:

Hartwig Medical Foundation Australia
Oliver Hofmann

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

Citations

You can cite the oncoanalyser zenodo record for a specific version using the following doi: 10.5281/zenodo.XXXXXXX

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: Stephen Watts
Login: scwatts
Kind: user

Website: https://stephen.ac
Repositories: 55
Profile: https://github.com/scwatts

Citation (CITATIONS.md)

# nf-core/oncoanalyser: 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

- [BCFtools](https://doi.org/10.1093/gigascience/giab008)

  > Danecek, P., Bonfield, J. K., Liddle, J., Marshall, J., Ohan, V., Pollard, M. O., Whitwham, A., Keane, T., McCarthy, S. A., Davies, R. M., & Li, H. (2021). Twelve years of SAMtools and BCFtools. GigaScience, 10(2), giab008. https://doi.org/10.1093/gigascience/giab008

- [BWA](https://doi.org/10.1093/bioinformatics/btp324)

  > Li, H., & Durbin, R. (2009). Fast and accurate short read alignment with Burrows–Wheeler transform. Bioinformatics, 25(14), 1754–1760. https://doi.org/10.1093/bioinformatics/btp324

- [bwa-mem2](https://doi.org/10.1109/IPDPS.2019.00041)

  > Vasimuddin, Md., Misra, S., Li, H., & Aluru, S. (2019). Efficient Architecture-Aware Acceleration of BWA-MEM for Multicore Systems. 2019 IEEE International Parallel and Distributed Processing Symposium (IPDPS), 314–324. https://doi.org/10.1109/IPDPS.2019.00041

- [CHORD](https://doi.org/10.1038/s41467-020-19406-4)

  > Nguyen, L., W. M. Martens, J., Van Hoeck, A., & Cuppen, E. (2020). Pan-cancer landscape of homologous recombination deficiency. Nature Communications, 11(1), 5584. https://doi.org/10.1038/s41467-020-19406-4

- [fastp](https://doi.org/10.1093/bioinformatics/bty560)

  > Chen, S., Zhou, Y., Chen, Y., & Gu, J. (2018). fastp: An ultra-fast all-in-one FASTQ preprocessor. Bioinformatics, 34(17), i884–i890. https://doi.org/10.1093/bioinformatics/bty560

- [GATK](https://doi.org/10.1093/bioinformatics/btp324)

  > McKenna, A., Hanna, M., Banks, E., Sivachenko, A., Cibulskis, K., Kernytsky, A., Garimella, K., Altshuler, D., Gabriel, S., Daly, M., & DePristo, M. A. (2010). The Genome Analysis Toolkit: A MapReduce framework for analyzing next-generation DNA sequencing data. Genome Research, 20(9), 1297–1303. https://doi.org/10.1101/gr.107524.110

- [GRIDSS2](https://doi.org/10.1186/s13059-021-02423-x)

  > Cameron, D. L., Baber, J., Shale, C., Valle-Inclan, J. E., Besselink, N., van Hoeck, A., Janssen, R., Cuppen, E., Priestley, P., & Papenfuss, A. T. (2021). GRIDSS2: Comprehensive characterisation of somatic structural variation using single breakend variants and structural variant phasing. Genome Biology, 22(1), Article 1. https://doi.org/10.1186/s13059-021-02423-x

- [LILAC](https://doi.org/10.1038/s41588-023-01367-1)

  > Martínez-Jiménez, F., Priestley, P., Shale, C., Baber, J., Rozemuller, E., & Cuppen, E. (2023). Genetic immune escape landscape in primary and metastatic cancer. Nature Genetics, 55(5), 820–831. https://doi.org/10.1038/s41588-023-01367-1

- [LINX](https://doi.org/10.1016/j.xgen.2022.100112)

  > Shale, C., Cameron, D. L., Baber, J., Wong, M., Cowley, M. J., Papenfuss, A. T., Cuppen, E., & Priestley, P. (2022). Unscrambling cancer genomes via integrated analysis of structural variation and copy number. Cell Genomics, 2(4). https://doi.org/10.1016/j.xgen.2022.100112

- [PURPLE](https://doi.org/10.1038/s41586-019-1689-y)

  > Priestley, P., Baber, J., Lolkema, M. P., Steeghs, N., de Bruijn, E., Shale, C., Duyvesteyn, K., Haidari, S., van Hoeck, A., Onstenk, W., Roepman, P., Voda, M., Bloemendal, H. J., Tjan-Heijnen, V. C. G., van Herpen, C. M. L., Labots, M., Witteveen, P. O., Smit, E. F., Sleijfer, S., … Cuppen, E. (2019). Pan-cancer whole-genome analyses of metastatic solid tumours. Nature, 575(7781), 210–216. https://doi.org/10.1038/s41586-019-1689-y

- [Sambamba](https://doi.org/10.1093/bioinformatics/btv098)

  > Tarasov, A., Vilella, A. J., Cuppen, E., Nijman, I. J., & Prins, P. (2015). Sambamba: Fast processing of NGS alignment formats. Bioinformatics, 31(12), 2032–2034. https://doi.org/10.1093/bioinformatics/btv098

- [SAMtools](https://doi.org/10.1093/gigascience/giab008)

  > Danecek, P., Bonfield, J. K., Liddle, J., Marshall, J., Ohan, V., Pollard, M. O., Whitwham, A., Keane, T., McCarthy, S. A., Davies, R. M., & Li, H. (2021). Twelve years of SAMtools and BCFtools. GigaScience, 10(2), giab008. https://doi.org/10.1093/gigascience/giab008

- [STAR](https://doi.org/10.1093/bioinformatics/bts635)

  > Dobin, A., Davis, C. A., Schlesinger, F., Drenkow, J., Zaleski, C., Jha, S., Batut, P., Chaisson, M., & Gingeras, T. R. (2013). STAR: Ultrafast universal RNA-seq aligner. Bioinformatics, 29(1), 15–21. https://doi.org/10.1093/bioinformatics/bts635

- [VIRUSBreakend](https://doi.org/10.1093/bioinformatics/btab343)

  > Cameron, D. L., Jacobs, N., Roepman, P., Priestley, P., Cuppen, E., & Papenfuss, A. T. (2021). VIRUSBreakend: Viral Integration Recognition Using Single Breakends. Bioinformatics, 37(19), 3115–3119. https://doi.org/10.1093/bioinformatics/btab343

## 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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