Genomic epidemiology & bioinformatics
graph-gene Caller (
ggCaller), combines gene annotation and pangenome clustering steps within population-wide de Bruijn Graphs. Using population-frequency information, ggCaller improves consistency of gene annotations, leading to more accurate clustering and significantly reduced run-times versus linear-genome based annotation and pangenome analysis.
ggcaller is written by Sam Horsfield, and in collaboration with Nicholas Croucher.
- Download (conda): https://anaconda.org/bioconda/ggcaller
- Paper (preprint): https://www.biorxiv.org/content/10.1101/2023.01.24.524926v1
- Documentation: https://ggcaller.readthedocs.io
- Code: https://github.com/samhorsfield96/ggCaller
SKA (version 2)
Split k-mer analysis (
SKA) can be used to produce alignments from closely related sequence assemblies or
reads, quickly (because it is alignment-free) and with minimal fuss (due to the interface).
This enables downstream analysis such as phylogenetics or sequence completeness.
In collaboration with Simon Harris.
- Download (cargo): https://crates.io/crates/ska
- Download (conda): https://anaconda.org/bioconda/ska
- Documentation: https://docs.rs/ska/latest
- Code: https://github.com/bacpop/ska.rust
List of databases is on the PopPUNK page.
Tools for bacterial genomic epidemiology. Quickly find core and accessory distances between whole-genome sequences, and use these to find genetically clusters. New data can be rapidly ‘queried’ against existing clusters, giving consistent nomenclature. In collaboration with Nicholas Croucher.
- Download (conda): https://anaconda.org/bioconda/poppunk
- Download (pip): https://pypi.org/project/poppunk/
- Paper: https://doi.org/10.1101/gr.241455.118
- Documentation: https://poppunk.readthedocs.io
- Code: https://github.com/bacpop/poppunk
Library of sketching functions used to rapidly calculate core and accessory distances between bacterial genomes. Designed as a faster drop-in back-end for PopPUNK, you can also use to replace mash (100x speedup, further 50x with GPUs).
- Download (conda): https://anaconda.org/bioconda/pp-sketchlib
- Code: https://github.com/bacpop/pp-sketchlib
Poplation analysis PIPEline. Designed to be run downstream of PopPUNK, to obtain subclusters and visualisations. A Snakemake pipeline that requires some config modifications to run.
- Code and download: https://github.com/bacpop/PopPIPE
- Documentation: https://poppunk.readthedocs.io/en/latest/subclustering.html
odin, dust and mcstate
A suite of R packages to assist in fast, reproducible state-space models, particularly compartmental models used in epidemiology. In collaboration with Rich Fitzjohn and RESIDE at MRC GIDA
odin: a domain-specific language that makes compartmental models easy to write, extend, and are fast to run:
dust: parallelised code for random number generation for Monte Carlo models, used to actually run state space models forward in time
mcstate: statistical support which allows running, forecasting and inference from these models
- Paper: https://wellcomeopenresearch.org/articles/5-288/v1
- Documentation: https://mrc-ide.github.io/mcstate/articles/sir_models.html (and links above)
Comprehensive pangenome-wide association studies in microbes. Find genetic variation that is linked to a phenotype or clone of interest. In collaboration with Marco Galardini.
- Download (conda): https://anaconda.org/bioconda/pyseer
- Download (pip): https://pypi.org/project/pyseer
- Paper: https://doi.org/10.1093/bioinformatics/bty539
- Documentation: https://pyseer.readthedocs.io
- Code: https://github.com/mgalardini/pyseer
Packages to count and determine presence of non-redundant sequence elements. Use ‘caller’ both to determine what the are unitigs in a population, and to quickly determine presence/absence in a new population. The ‘counter’ is no longer supported, but is an alternative to the first purpose.
- unitig-caller (github): https://github.com/bacpop/unitig-caller
- unitig-caller (conda): https://anaconda.org/bioconda/unitig-caller
(no longer supported)
- unitig-counter (github): https://github.com/bacpop/unitig-counter
- unitig-counter (conda): https://anaconda.org/bioconda/unitig-counter
SEER (no longer supported)
First version of software for association studies in bacteria (superseded by pyseer, above). Find k-mers that are linked to a phenotype of interest.
- Download (conda): https://anaconda.org/bioconda/seer
- Download (github): https://github.com/johnlees/seer/releases
- Paper: https://doi.org/10.1038/ncomms12797
- Documentation: https://github.com/johnlees/seer/wiki
- Code: https://github.com/johnlees/seer
Rapid stochastic cluster embedding (like t-SNE, UMAP) for genetic distances, particularly pathogen genome sequences. In collaboration with Gerry Tonkin-Hill.
- Download (conda): https://anaconda.org/conda-forge/mandrake
- Preprint: https://www.biorxiv.org/content/10.1101/2021.10.28.466232v1
- Documentation: https://mandrake.readthedocs.io/en/latest/
- Code: https://github.com/bacpop/mandrake
A search engine for bacterial genomes and metadata.
- Front-end: https://github.com/bacpop/BacQuerya
- API (middle layer): https://github.com/bacpop/BacQuerya-api
- Sequence processing: https://github.com/bacpop/BacQuerya-processing
An in-browser AMR prediction tool for Streptococcus pneumoniae.
- Front-end: https://github.com/bacpop/AMR_ReactApp
- WebAssembly: https://github.com/bacpop/AMR_prediction
A WebAssembly version of the mandrake stochastic cluster embedding tool. Written by Gerry Tonkin-Hill.