February 13th, 2017

Launch of VICTOR, the Virus Classification and Tree Building Online Resource

Our novel web service compares bacterial and archaeal viruses ("phages") using either their genome or proteome sequences. The results include phylogenomic trees inferred using the Genome-BLAST Distance Phylogeny method (GBDP), with branch support, as well as suggestions for the classification at the species, genus and family level. The methods were validated against a comprehensive taxonomic reference dataset accepted by the ICTV with respect to phylogenetic as well as clustering algorithms. We are confident that this service will be beneficial for phage taxonomy in particular as well as for a deeper understanding of phage evolution in general. Further information on the scientific background, the underlying paper etc. are found in the VICTOR FAQ.

March 3rd, 2016

Beside the option to reliably calculate accurate genome sequence-based DDH estimates and intergenomic distances via the GGDC 2.1, many users also asked for a complementary option to calculate gene similarities (e.g., of the 16S rRNA gene) and/or phylogenies with state-of-the-art methods. Thus, we made our DSMZ in-house phylogeny pipeline available via the GGDC website, augmenting it with a service for inferring phylogenies and/or pairwise similarities from single genes. Regarding pairwise similarities, please note that these are calculated under the recommended settings proposed in Meier-Kolthoff et al. (2013) which even allow for the application of phylum-specific 16s similarity thresholds, as introduced in the aforementioned study (also available as a free local copy). Accordingly, we have divided the FAQ into two parts, one for the GGDC as before, and a new one for the single-gene part.

January 14th, 2016

Happy New Year! We increased the FASTA file limit from 10 to 50 as well as clearly simplified file upload handling. The use of the GGDC 2.1 should now be much simpler! If you want to conduct larger analyses that do not fit into the scope of the web form, please contact us.

Another new feature of the GGDC is the reporting of the percent G+C difference between two given genomes. Based on the results of our 2014 IJSEM publication, 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), thus representing a valuable asset in the taxonomist's toolchain.

January 10th, 2015

A nice example for the use of the GGDC is the recent discovery of a new class of antibiotics.

December 8th, 2014

As of today, the GGDC 2 can also be used to delineate microbial subspecies. The rationale behind this is explained in our recent study.

February 21st, 2013

The GGDC 2 has been released!

GGDC 2 is an updated and enhanced version with improved DDH-prediction models and additional features such as confidence-interval estimation. To the best of our knowledge, it is the only digital DDH method that provides this feature. Of all genome-based methods we are aware of, GGDC 2 yields the highest correspondence to traditional DDH (without sharing its drawbacks). Details are described in our BMC Bioinformatics study.

March, 18th 2010

The Genome-to-Genome Distance Calculator version 1 (GGDC 1.0) has been released!

Even though, the pragmatic species concept for Bacteria and Archaea is ultimately based on DNA-DNA hybridization (DDH), the conventional ("wet-lab") approach is quite tedious, error-prone and can only be conducted in a few specialized labs. Here, as a solution, the GGDC reliably calculates accurate digital DNA:DNA hybridization estimates (dDDH values) between pairs of genome sequences, without mimicking the pitfalls of conventional DDH. The GGDC tool, based on the approach of Henz et al. (2005), yielded slightly to significantly higher correlations with conventionally determined DDH than the average nucleotide identity implementation (Konstantinidis & Tiedje, 2005). This is crucial, as agreement with the conventional DDH standard, on average, is the main criterion for the success of genome sequence-based methods (Stackebrandt et al., 2002); otherwise species boundaries estimated with sequence-based methods were not consistent with earlier ones estimated conventionally. More information is found in the Background section and in our accompanying publications (Auch et al. 2010a, Auch et al. 2010b).