Dnabarcoder is an open-source software package for analyzing reference datasets, similarity cutoff calculation and classification.
Welcome to DNA barcoder and thank you for choosing this application for your metabarcoding classification! Interested in how this application is different from the others? Go to the about page!
The main focus of DNA barcoder is to classify based on similarity cutoffs. A similarity cutoff is a percentage at which an unidentified sequence and a reference sequence have to minimally coincide. This can be given as a global value or local values. A global similarity cutoff is representative for the whole reference dataset. Local similarity cutoffs are given per taxonomic group. Local similarity cutoffs will generally give more accurate classification results, but will take more time to compute. Similarity cutoffs can be calculated on the cutoff calculation page.
Sequences can be classified with the computed similarity cutoffs on the classification page. One of the standard reference ITS datasets or your own dataset can be used.
After classification phylogenetic trees can be generated based on the results. Such a tree will contain a classified sequence and the sequences from the reference dataset with the same taxonomy as the sequence was classified for. This can be used as verification for the classification result.
DNA barcoder also has options for analysis and visualization. On the analysis pages under the "Reference sequences" tab a dataset can be analysed based on length and taxonomy. Here a similarity matrix can also be created of a dataset. On the visualization page a reference dataset can be visualized three-dimensionally.