Poster Open Access
Metagenomics is a powerful approach to study genetic content of environmental samples and it has been strongly promoted by Next-Generation Sequencing technologies. The aim of metagenomic classification is to assign each sequence of the metagenome to a corresponding taxonomic unit, or to classify it as “novel”.
To cope with increasingly large metagenomic projects, researchers resort to alignment-free methods. The most popular tool – Kraken – provides an extremely rapid read classification, but its index suffers from two major limitations: an enormous memory consumption and a lossy k-mer representation through their lowest common ancestors.
We present Prophyle, a metagenomic classifier based on the Burrows-Wheeler Transform. ProPhyle uses a classification algorithm similar to Kraken but with an indexing strategy based on a bottom-up propagation of k-mers in the tree, assembling contigs at each node and matching using a standard full-text search. The obtained index occupies only a fraction of RAM compared to Kraken – 13 GB instead of 90 GB for index construction and 14 GB instead of 72 GB for index querying. The resulting index is also more expressive, allowing users to retrieve a list of all genomes for every queried k-mer. Overall, ProPhyle provides an index for resource-frugal metagenomic classification, which is accurate even with single-species phylogenetic trees. Prophyle is available at http://github.com/karel-brinda/prophyle, released under the MIT license.