Pakket: kraken2 (2.1.3-1)
Verwijzigingen voor kraken2
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Het bronpakket kraken2 downloaden:
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Externe bronnen:
- Homepage [www.ccb.jhu.edu]
Vergelijkbare pakketten:
taxonomic classification system using exact k-mer matches
Kraken 2 is the newest version of Kraken, a taxonomic classification system using exact k-mer matches to achieve high accuracy and fast classification speeds. This classifier matches each k-mer within a query sequence to the lowest common ancestor (LCA) of all genomes containing the given k-mer. The k-mer assignments inform the classification algorithm. [see: Kraken 1's Webpage for more details].
Kraken 2 provides significant improvements to Kraken 1, with faster database build times, smaller database sizes, and faster classification speeds. These improvements were achieved by the following updates to the Kraken classification program:
1. Storage of Minimizers: Instead of storing/querying entire k-mers, Kraken 2 stores minimizers (l-mers) of each k-mer. The length of each l-mer must be ≤ the k-mer length. Each k-mer is treated by Kraken 2 as if its LCA is the same as its minimizer's LCA. 2. Introduction of Spaced Seeds: Kraken 2 also uses spaced seeds to store and query minimizers to improve classification accuracy. 3. Database Structure: While Kraken 1 saved an indexed and sorted list of k-mer/LCA pairs, Kraken 2 uses a compact hash table. This hash table is a probabilistic data structure that allows for faster queries and lower memory requirements. However, this data structure does have a <1% chance of returning the incorrect LCA or returning an LCA for a non-inserted minimizer. Users can compensate for this possibility by using Kraken's confidence scoring thresholds. 4. Protein Databases: Kraken 2 allows for databases built from amino acid sequences. When queried, Kraken 2 performs a six-frame translated search of the query sequences against the database. 5. 16S Databases: Kraken 2 also provides support for databases not based on NCBI's taxonomy. Currently, these include the 16S databases: Greengenes, SILVA, and RDP.
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