K-mer dictionary uses variable segment lengths proportional to genomes size and ranging from 200-8000 nt.

Sequential segments and selecting 32-mers to represent each segment. K-mer dictionaries were built by computationally slicing reference genomes into

The database contained 2,383,364 taxonomy nodes in March 2020. Reference sequences were mapped to the taxonomy hierarchy using the NCBI Taxonomy database. Supplemented with the viral genome set from nt and used as the source for k-mer creation in both 'coarse' and 'fine' sets. They were merged at the lowest common taxonomic node as above. K-mers was determined by searching against the source reference genomic database. Finally, the specificity of representative Were 'merged' at the lowest common taxonomic node shared between references. AAAAAA or ACACACACACA) were filtered from dictionaries, and discrete k-mers belonging to multiple taxonomic references Low complexity k-mers composed of >50% homo-polymer or dinucleotide repeats Specificity and accuracy of STAT results. Several strategies were used to enhance the Segment are selected based on minimum fvn1 hash function. STAT k-mer dictionaries are built using an iterative minhash based approach against reference genomic databases.įor every fixed segment length of incoming reference nucleotide sequence, k-mer representing this When multiple tax nodes are mapped for single spot, we use the lowest non-ambiguous mapping. Reference dictionary database are used to compute distribution of reads between identified taxonomy classes (species and higher order taxonomy nodes). In the second pass, organism-specific slices from a 'fine' Used to identify organisms matching a read set. In the first pass, a small, 'coarse' reference dictionary database is To precomputed k-mer dictionary databases. STAT maps sequencing reads to a taxonomic hierarchy using a two-step strategy based on exact query read matches Sequencing reads to a taxonomic hierarchy and reports the taxonomic composition of reads within a sequencing run. The NCBI SRA Taxonomy Analysis Tool (STAT) calculates the taxonomic distribution of reads from next generation sequencing runs.

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