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rebar

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rebar is a REcombination BARcode detector!

Why rebar?

  1. rebar detects and visualizes genomic recombination.

    It follows the PHA4GE Guidance for Detecting and Characterizing SARS-CoV-2 Recombinants which outlines three steps:

    1. Assess the genomic evidence for recombination.
    2. Identify the breakpoint coordinates and parental regions.
    3. Classify sequences as designated or novel recombinant lineages.
  2. rebar peforms generalized clade assignment.

    While specifically designed for recombinants, rebar works on non-recombinants tool! It will report a sequence's closest known match in the dataset, as well any mutation conflicts that were observed. The linelist and visual outputs can be used to detect novel variants, such as the SARS-CoV-2 pango-designation process.

  3. rebar is for exploring hypotheses.

    The recombination search can be customized to test your hypotheses about which parents and genomic regions are recombining. If that sounds overwhelming, you can always just use the pre-configured datasets (ex. SARS-CoV-2) that are validated against known recombinants.

A plot of the breakpoints and parental regions for the recombinant SARS-CoV-2 lineage XBB.1.16. At the top are rectangles arranged side-by-side horizontally. These are colored and labelled by each parent (ex. BJ.1., CJ.1) and are intepreted as reading left to right, 5' to 3'. Below these regions are genomic annotations, which show the coordinates for each gene. At the bottom are horizontal tracks, where each row is a sample, and each column is a mutation. Mutations are colored according to which parent the recombination region derives from.

Install

rebar is a standalone binary file, we recommend conda or direct download.

conda install -c bioconda rebar
  • Please see the install docs for Windows, macOS, Docker, Singularity, and Conda.
  • Please see the compile docs for those interested in source compilation.

Usage

Custom Dataset

A small, test dataset (toy1) serves as a template for creating custom datasets, and for easer visualization of the method and output.

rebar dataset download --name toy1 --tag custom --output-dir dataset/toy1
rebar run --dataset-dir dataset/toy1 --populations "*" --mask 0,0 --min-length 3 --output-dir output/toy1
rebar plot  --run-dir output/toy1 --annotations dataset/toy1/annotations.tsv

SARS-CoV-2

Download a SARS-CoV-2 dataset, version-controlled to the date 2023-11-30 (try any date!).

rebar dataset download --name sars-cov-2 --tag 2023-11-30 --output-dir dataset/sars-cov-2/2023-11-30
rebar run --dataset-dir dataset/sars-cov-2/2023-11-30  --populations "AY.4.2*,BA.5.2,XBC.1.6*,XBB.1.5.1,XBL" --output-dir output/sars-cov-2
rebar plot --run-dir output/sars-cov-2 --annotations dataset/sars-cov-2/2023-11-30/annotations.tsv

Other

Please see the examples docs for more tutorials including:

  • Using your own alignment of genomes as input.
  • Testing specific parent combinations.
  • Performing a 'knockout' experiment.
  • Validating all populations in a dataset.

Please see the dataset and run docs for more methodology.

Output

Linelist

A linelist summary of results (ex. output/toy1/linelist.tsv).

strain validate validate_details population recombinant parents breakpoints edge_case unique_key regions genome_length dataset_name dataset_tag cli_version
population_A pass A false 20 toy1 custom 0.2.0
population_B pass B false 20 toy1 custom 0.2.0
population_C pass C false 20 toy1 custom 0.2.0
population_D pass D D A,B 12-12 false D_A_B_12-12 1-11|A,12-20|B 20 toy1 custom 0.2.0
population_E pass E E C,D 4-4 false E_C_D_4-4 1-3|C,4-20|D 20 toy1 custom 0.2.0

Plots

A visualization of substitutions, parental origins, and breakpoints (ex. output/toy1/plots/).

rebar plot of population D in dataset toy1

Barcodes

The discriminating sites with mutations between samples and their parents (ex. output/toy1/barcodes/).

coord origin Reference A B population_D
1 A A C T C
2 A A C T C
3 A A C T C
4 A A C T C
5 A A C T C
... ... ... ... ... ...

Credits

rebar is built and maintained by Katherine Eaton at the National Microbiology Laboratory (NML) of the Public Health Agency of Canada (PHAC).

This project follows the all-contributors specification (emoji key). Contributions of any kind welcome!


Katherine Eaton

πŸ’» πŸ“– 🎨 πŸ€” πŸš‡ 🚧

Special thanks go to the following people, who are instrumental to the design and data sources in rebar:


Lena Schimmel

πŸ€”

Cornelius Roemer

πŸ”£ πŸ”£ πŸ”£

Josh Levy

πŸ”£

Richard Neher

πŸ€”

Thanks go to the following people, who participated in the development of rebar and ncov-recombinant:


Yatish Turakhia

πŸ”£ πŸ€”

Angie Hinrichs

πŸ”£ πŸ€”

Benjamin Delisle

πŸ› ⚠️

Vani Priyadarsini Ikkurthi

πŸ› ⚠️

Mark Horsman

πŸ€” 🎨

Dan Fornika

πŸ€” ⚠️

Tara Newman
πŸ€” ⚠️

Adrian Zetner

πŸ”£ πŸ€”

Connor Chato

πŸ”£ πŸ€”

Matthew Wells

πŸ“¦

Andrea Tyler

πŸ”£