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stitchimpute

Pipeline that uses STITCH for imputing genotypes from low-coverage NGS data in a population.

https://github.com/birneylab/stitchimpute

Science Score: 44.0%

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Repository

Pipeline that uses STITCH for imputing genotypes from low-coverage NGS data in a population.

Basic Info
  • Host: GitHub
  • Owner: birneylab
  • License: mit
  • Language: Jupyter Notebook
  • Default Branch: main
  • Size: 32.4 MB
Statistics
  • Stars: 6
  • Watchers: 2
  • Forks: 0
  • Open Issues: 1
  • Releases: 4
Created over 2 years ago · Last pushed over 1 year ago
Metadata Files
Readme Changelog Contributing License Code of conduct Citation

README.md

birneylab/stitchimpute birneylab/stitchimpute

Nextflow run with conda run with docker run with singularity

Introduction

birneylab/stitchimpute is a bioinformatics pipeline that uses STITCH for imputing genotypes from low-coverage NGS data in a population. It can also help in the selection of the ideal parameters for the imputation, and in the refinement of the SNP set used. It can compare the imputation results against some ground truth (i.e. high-coverage samples) for performance evaluation and parameter/SNP set refinement.

Disclaimer: this pipeline uses the nf-core template but it is not part of nf-core itself.

birneylab/stitchimpute

  1. Downsample high-coverage cram files (samtools; optional)
  2. Run joint imputation with STITCH on high and low coverage cram files (STITCH)
  3. Compare imputation results to ground truth variants (glimpse2 concordance; optional)
  4. Plot imputation performance stats (ggplot2)

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,cram,crai sample1,/path/to/sample1.cram,/path/to/sample1.cram.crai sample2,/path/to/sample2.cram,/path/to/sample2.cram.crai

Each row represents a sample with its associated cram file and crai file.

Now, you can run the pipeline using:

bash nextflow run birneylab/stitchimpute \ -profile <docker/singularity/.../institute> \ --input samplesheet.csv \ --outdir <OUTDIR>

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

birneylab/stitchimpute was originally written by Saul Pierotti.

Citations

An extensive list of references for the tools used by the pipeline can be found in the CITATIONS.md file.

The main citation for birneylab/stitchimpute is:

Genotype imputation in F2 crosses of inbred lines

Saul Pierotti, Bettina Welz, Mireia Osuna-López, Tomas Fitzgerald, Joachim Wittbrodt, Ewan Birney

Bioinformatics Advances, Volume 4, Issue 1, 2024, doi: 10.1093/bioadv/vbae107

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: birneylab
  • Login: birneylab
  • Kind: organization

Citation (CITATIONS.md) 

# birneylab/stitchimpute: Citations

## birneylab/[stitchimpute](https://doi.org/10.1101/2023.12.12.571258)

> Saul Pierotti, Bettina Welz, Mireia Osuna-López, Tomas Fitzgerald, Joachim Wittbrodt, Ewan Birney. Genotype imputation in F2 crosses of inbred lines. _Bioinformatics Advances_, Volume 4, Issue 1, 2024, doi: [10.1093/bioadv/vbae107](https://doi.org/10.1093/bioadv/vbae107)

## [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

- [STITCH](https://github.com/rwdavies/STITCH)

  > Davies, R., Flint, J., Myers, S. et al. Rapid genotype imputation from sequence without reference panels. Nat Genet 48, 965–969 (2016). https://doi.org/10.1038/ng.3594

- [Samtools and Bcftools](http://www.htslib.org/)

  > Danecek P, Bonfield JK, Liddle J, Marshall J, Ohan V, Pollard MO, Whitwham A, Keane T, McCarthy SA, Davies RM, Li H, Twelve years of SAMtools and BCFtools, GigaScience (2021) 10(2) giab008 [33590861]

- [GLIMPSE2](https://odelaneau.github.io/GLIMPSE/)

  > Rubinacci, S., Ribeiro, D. M., Hofmeister, R. J., & Delaneau, O. (2021). Efficient phasing and imputation of low-coverage sequencing data using large reference panels. Nat. Genet., 53, 120–126. doi: 10.1038/s41588-020-00756-0

- [data.table](https://rdatatable.gitlab.io/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

- [tidyverse](https://www.tidyverse.org/)

  > H. Wickham. ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York, 2016
  > Wickham H, François R, Henry L, Müller K, Vaughan D (2023). dplyr: A Grammar of Data Manipulation. https://dplyr.tidyverse.org, https://github.com/tidyverse/dplyr.

- [R](https://www.r-project.org/)

  > R Core Team (2023). _R: A Language and Environment for Statistical Computing_. R Foundation for Statistical Computing, Vienna, Austria. <https://www.R-project.org/>.

## 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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Dependencies

modules/nf-core/bcftools/concat/meta.yml cpan
modules/nf-core/bcftools/index/meta.yml cpan
modules/nf-core/bcftools/query/meta.yml cpan
modules/nf-core/cat/cat/meta.yml cpan
modules/nf-core/custom/dumpsoftwareversions/meta.yml cpan
modules/nf-core/glimpse2/concordance/meta.yml cpan
modules/nf-core/samtools/coverage/meta.yml cpan
modules/nf-core/samtools/faidx/meta.yml cpan
modules/nf-core/samtools/index/meta.yml cpan
modules/nf-core/samtools/view/meta.yml cpan
modules/nf-core/stitch/meta.yml cpan
pyproject.toml pypi