https://github.com/esteinig/sketchy
Genomic neighbor typing of bacterial pathogens using MinHash :rat:
https://github.com/esteinig/sketchy
bacterial-genomes bioinformatics finch genomic-neighbor-typing mash minhash nanopore rust-lang
Last synced: over 1 year ago
JSON representation
Genomic neighbor typing of bacterial pathogens using MinHash :rat:
- Host: GitHub
- URL: https://github.com/esteinig/sketchy
- Owner: esteinig
- License: mit
- Created: 2019-03-03T01:01:45.000Z (over 7 years ago)
- Default Branch: master
- Last Pushed: 2023-01-10T22:25:29.000Z (over 3 years ago)
- Last Synced: 2025-04-06T15:53:18.158Z (over 1 year ago)
- Topics: bacterial-genomes, bioinformatics, finch, genomic-neighbor-typing, mash, minhash, nanopore, rust-lang
- Language: Rust
- Homepage:
- Size: 20 MB
- Stars: 44
- Watchers: 6
- Forks: 3
- Open Issues: 2
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# sketchy 
Genomic neighbor typing for lineage and genotype inference
## Overview
**`v0.6.0`**
`Sketchy` is a lineage calling and genotyping tool based on the heuristic principle of genomic neighbor typing developed by [Karel Břinda and colleagues (2020)](https://www.biorxiv.org/content/10.1101/403204v2). It queries species-wide ('hypothesis-agnostic') reference sketches using MinHash and infers associated genotypes based on the closest match, including multi-locus sequence types, susceptibility profiles, virulence factors or other genome-associated features provided by the user. Unlike the original implementation in [`RASE`](https://github.com/c2-d2/rase-pipeline), `sketchy` does not use phylogenetic trees which has some downsides, e.g. for sublineage genotype predictions (see below).
See the [latest docs](https://esteinig.github.io/sketchy) for install, usage and database building.
## Install
Cargo:
```
cargo install sketchy
```
BioConda:
```
conda install -c bioconda sketchy
```
[Release binaries](https://github.com/esteinig/sketchy/releases) available for download. Reference sketches can be constructed from local [assembly and genotype collections](https://esteinig.github.io/sketchy/#local-sketches). *S. aureus* reference sketches are available in the data availability section below.
## Strengths and limitations
* Reference sketches and genotype indices can be constructed easily from large genotype collections
* `Sketchy` requires few resources when using small sketch sizes (`s = 1000`)
* `Sketchy` performs best on lineage predictions and lineage-wide genotypes from very few reads - we found that tens to hundreds of reads can often give a good idea of the close matches in the reference sketch (especially when inspecting the top matches using `--top`)
However:
* Clade-specific genotype resolution is not as good as when using phylogenetic guide trees (`RASE`)
* Sketch size can be increased to increase performance (`s = 10000`), but resources scale approximately linearly
* `Sketchy` genotype inference may be difficult for species with high rates of homologous recombination
## Data availability
* Reference sketches and genotype files (`s = 1000`, `s = 10000`, `k = 16`) for [*S. aureus*](https://cloudstor.aarnet.edu.au/plus/s/3EBgvXi6sVHW8Ne) (full genotypes including susceptibility predictions and other genotypes), *S. pneumoniae*, *K. pneumoniae*, *P. aeruginosa* and *Neisseria spp.* (MLST) can be found in the [data repository](https://cloudstor.aarnet.edu.au/plus/s/rL0RHYunqhRK3i1).
* Reference sketches for cross-validation on the simulated species data can be found in this [data repository](https://cloudstor.aarnet.edu.au/plus/s/7ICPoSru6s6EHNY); genome assemblies for all species extracted from the ENA reference collection are available in this [data repository](https://cloudstor.aarnet.edu.au/plus/s/Td3ahBCPP2YAhCU)
* Scripts to extract data from the ENA collections [Grace Blackwell et al.](https://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.3001421) and compute reference metrics can be found in the [scripts directory](scripts/).
* Nanopore reads for the outbreak isolates and genotype surveillance panels in Papua New Guinea (Flongle, Goroka, sequential protocol) are available for download in the [data repository](https://cloudstor.aarnet.edu.au/plus/s/MFkirfq1N6uIosc). Raw sequence data (Illumina / ONT) is being uploaded to NCBI (PRJNA657380).
## Preprint
If you use `sketchy` for research and other applications, please cite:
> Steinig et al. (2022) - Genomic neighbor typing for bacterial outbreak surveillance - bioRxiv 2022.02.05.479210; doi: https://doi.org/10.1101/2022.02.05.479210