CGRclust: Chaos Game Representation for twin contrastive clustering of unlabelled DNA sequences
CGRclust is a novel, scalable, alignment-free DNA sequence clustering method that uses CGR images of DNA sequences and CNNs for twin contrastive clustering of unlabelled primary DNA sequences, achieving superior or comparable accuracy and performance over current approaches. CGRclust demonstrated enhanced reliability, by consistently achieving over 80% accuracy in more than 90% of the datasets analyzed. In particular, CGRclust performed especially well in clustering viral DNA datasets, where it consistently outperformed all competing methods.
Authors
- Kathleen A. Hill (ORCID: https://orcid.org/0000-0002-7788-5105)
- Lila Kari (ORCID: https://orcid.org/0000-0001-5700-5353)
- Fatemeh Alipour (ORCID: https://orcid.org/0000-0002-9413-3538)
Institutions
- Western University (CA)
- University of Waterloo (CA)
Publication Details
- Journal
- BMC Genomics
- Published
- 2024-12-18
- DOI
- https://doi.org/10.1186/s12864-024-11135-y
- Citations
- 5
- Primary Topic
- Fractal and DNA sequence analysis
- Type
- article
- Field-Weighted Citation Impact
- 1.17
Funders
- Compute Canada
- Natural Sciences and Engineering Research Council of Canada