Skip to main content

Genomic redundancy removal tool for cblaster hit sets

Project description

CAGEcleaner

install with bioconda Conda Manuscript DOI

[!NOTE] CAGEcleaner supports all functional cblaster modes (remote, local, hmm). We do not recommend using one of the combi modes as we have found bugs in it.

[!TIP] CAGEcleaner will be integrated into cblaster! You can already check out the development version at this fork (currently integrates CAGECleaner v1.2.3).

Outline

CAGEcleaner removes genomic redundancy from gene cluster hit sets identified by cblaster. The redundancy in target databases used by cblaster often propagates into the result set, requiring extensive manual curation before downstream analyses and visualisation can be carried out.

Given a session file from a cblaster run (or from a CAGECAT run), CAGEcleaner retrieves all hit-associated genome assemblies, groups these into assembly clusters by ANI and identifies a representative assembly for each assembly cluster using skDER. In addition, CAGEcleaner can retain hits that are divergent at the gene cluster level but are associated with non-representative genomes. Finally, CAGEcleaner returns a filtered cblaster session file as well as a list of retained gene cluster IDs for more straightforward downstream analysis.

workflow

Installation and more

For installation instructions, usage, explanations and more, head over to the CAGEcleaner wiki!

[!IMPORTANT] CAGEcleaner has no direct Windows support. If you seem to have it installed successfully on your Windows system, you probably have just installed v1.1.0, an old version with known bugs! There are alternative options to run CAGEcleaner on Windows.

Citations

If you found CAGEcleaner useful, please cite our manuscript:

De Vrieze, L., Biltjes, M., Lukashevich, S., Tsurumi, K., Masschelein, J. (2025) CAGEcleaner: reducing genomic redundancy in gene cluster mining. Bioinformatics https://doi.org/10.1093/bioinformatics/btaf373

CAGEcleaner relies heavily on the skDER genome dereplication tool and its main dependency skani, so please give these proper credit as well.

Salamzade, R., & Kalan, L. R. (2023). skDER: microbial genome dereplication approaches for comparative and metagenomic applications. bioRxiv https://doi.org/10.1101/2023.09.27.559801`
Shaw, J., & Yu, Y. W. (2023). Fast and robust metagenomic sequence comparison through sparse chaining with skani. Nature Methods, 20(11), 1661–1665. https://doi.org/10.1038/s41592-023-02018-3

License

CAGEcleaner is freely available under an MIT license.

Use of the third-party software, libraries or code referred to in the References section above may be governed by separate terms and conditions or license provisions. Your use of the third-party software, libraries or code is subject to any such terms and you should check that you can comply with any applicable restrictions or terms and conditions before use.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

cagecleaner-1.3.1.tar.gz (22.9 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

cagecleaner-1.3.1-py3-none-any.whl (22.4 kB view details)

Uploaded Python 3

File details

Details for the file cagecleaner-1.3.1.tar.gz.

File metadata

  • Download URL: cagecleaner-1.3.1.tar.gz
  • Upload date:
  • Size: 22.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.0.1 CPython/3.10.0

File hashes

Hashes for cagecleaner-1.3.1.tar.gz
Algorithm Hash digest
SHA256 25f45c5c0db13177c080033f927aa473a92b1351e9632949766fee1784a27f3e
MD5 e5e10503d3838f05b32bc2846a67910c
BLAKE2b-256 12cea76d2c0c15a03a69134098951615d01c9c6a42c618d19afd077fc8b23124

See more details on using hashes here.

File details

Details for the file cagecleaner-1.3.1-py3-none-any.whl.

File metadata

  • Download URL: cagecleaner-1.3.1-py3-none-any.whl
  • Upload date:
  • Size: 22.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.0.1 CPython/3.10.0

File hashes

Hashes for cagecleaner-1.3.1-py3-none-any.whl
Algorithm Hash digest
SHA256 7175809376cf72836655e4b3db4d921577fc876b62b22ff259821229d1728247
MD5 abd4e2b4a74cca468bc5e8a308453b5c
BLAKE2b-256 2abf3f9a25d4bcfa434dce0e764c8591cc848ed7f292b31b4d92348ca6cd9ae2

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page