GGDC

GGDC

The pragmatic species concept for Bacteria and Archaea is ultimately based on DNA-DNA hybridization (DDH), a method known to be tedious. The GGDC is a state-of-the-art in silico method for genome-to-genome comparison, thus reliably mimicking conventional DDH, except for its pitfalls.

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VICTOR

VICTOR

Virus taxonomy should be strongly informed by sequence-based methods. The web service VICTOR compares phages using their genome or proteome sequences. Results include phylogenomic trees with branch support and suggestions for the classification at the species, genus and family level.

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Gene Phylogeny and Similarities

Phylogeny Service

A service which (i) infers maximum-likelihood and maximum-parsimony phylogenies using state-of-the-art methods and (ii) calculates exact pairwise similarities between gene sequences under settings qualifying for the application of phylum-specific 16S similarity thresholds.

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Digital DNA:DNA hybridization. Very reliable in silico method.

GGDC yielded higher correlations with wet-lab DDH (without mimicking its pitfalls) than other in silico approaches. GGDC uses statistical models that considerably improve on the linear models used by other approaches (e.g. ANI). A practical advantage of GGDC over ANI is that GGDC operates on the same scale than wet-lab DDH values, which makes comparisons much easier.

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Truly whole genome-based phylogenies.

The Genome BLAST Distance Phylogeny (GBDP) approach for calculating accurate intergenomic distances, the core of the GGDC, was originally developed to infer genome-based phylogenies. Its latest version allows for the inference of branch support and this has been successfully utilized in a number of important studies.

KMG-1 
tree

Difference in genomic G+C content. Make use of it.

In contrast to DDH dissimilarities, differences in percent genomic G+C content between distinct species can be quite close to zero. They just cannot be larger than 1 within the same species (Meier-Kolthoff et al. 2014). Here, the GGDC helps users to easily obtain this information and to use it for species description.

G+C content model