Automated download and clean-up of family-specific databases for kmer-based virus identification.

SUMMARY: Here, we present an automated pipeline for Download Of NCBI Entries (DONE) and continuous updating of a local sequence database based on user-specified queries. The database can be created with either protein or nucleotide sequences containing all entries or complete genomes only. The pipeline can automatically clean the database by removing entries with matches to a database of user-specified sequence contaminants. The default contamination entries include sequences from the UniVec database of plasmids, marker genes and sequencing adapters from NCBI, an E.coli genome, rRNA sequences, vectors and satellite sequences. Furthermore, duplicates are removed and the database is automatically screened for sequences from green fluorescent protein, luciferase and antibiotic resistance genes that might be present in some GenBank viral entries, and could lead to false positives in virus identification. For utilizing the database, we present a useful opportunity for dealing with possible human contamination. We show the applicability of DONE by downloading a virus database comprising 37 virus families. We observed an average increase of 16 776 new entries downloaded per month for the 37 families. In addition, we demonstrate the utility of a custom database compared to a standard reference database for classifying both simulated and real sequence data. AVAILABILITYAND IMPLEMENTATION: The DONE pipeline for downloading and cleaning is deposited in a publicly available repository (https://bitbucket.org/genomicepidemiology/done/src/master/). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online

Critical Assessment of Metagenome Interpretation: the second round of challenges.

Evaluating metagenomic software is key for optimizing metagenome interpretation and focus of the Initiative for the Critical Assessment of Metagenome Interpretation (CAMI). The CAMI II challenge engaged the community to assess methods on realistic and complex datasets with long- and short-read sequences, created computationally from around 1,700 new and known genomes, as well as 600 new plasmids and viruses. Here we analyze 5,002 results by 76 program versions. Substantial improvements were seen in assembly, some due to long-read data. Related strains still were challenging for assembly and genome recovery through binning, as was assembly quality for the latter. Profilers markedly matured, with taxon profilers and binners excelling at higher bacterial ranks, but underperforming for viruses and Archaea. Clinical pathogen detection results revealed a need to improve reproducibility. Runtime and memory usage analyses identified efficient programs, including top performers with other metrics. The results identify challenges and guide researchers in selecting methods for analyses