A database of phylogenetically atypical genes in archaeal and bacterial genomes, identified using the DarkHorse algorithm
2008

DarkHorse: A Database for Identifying Unusual Genes in Microbial Genomes

Sample size: 955 publication Evidence: moderate

Author Information

Author(s): Sheila Podell, Terry Gaasterland, Eric E. Allen

Primary Institution: Scripps Institution of Oceanography, University of California at San Diego

Hypothesis

The DarkHorse algorithm can effectively identify phylogenetically atypical genes in microbial genomes.

Conclusion

The DarkHorse HGT Candidate database is a powerful tool for identifying atypical proteins and exploring horizontal gene transfer patterns.

Supporting Evidence

  • The DarkHorse algorithm processes large numbers of genomes efficiently.
  • It provides a web-searchable database for exploring horizontal gene transfer.
  • The algorithm uses lineage probability index scores to identify atypical genes.

Takeaway

The DarkHorse database helps scientists find unusual genes in bacteria and archaea, which can show how genes move between different organisms.

Methodology

The DarkHorse algorithm was applied to 955 microbial genomes to identify atypical genes using lineage probability index scores.

Limitations

The algorithm cannot provide definitive proof of horizontal gene transfer by itself.

Digital Object Identifier (DOI)

10.1186/1471-2105-9-419

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