engleski

Benchmarking metagenomic classification tools for long read sequencing data

In recent years, both long-read sequencing and metagenomic analysis have been significantly advanced. Although long-read sequencing technologies have been primarily used for de novo genome assembly, they are rapidly maturing for widespread use in other applications. In particular, long reads could potentially lead to more precise taxonomic identification which has sparked an interest in using them for metagenomic analysis. Here we present a benchmark of several tools for metagenomic taxonomic classification, tested on in- silico datasets that were constructed using real long reads from isolate sequencing. We compared tools that were either newly developed for or modified to work with long reads, including Kraken, Centrifuge, CLARK, MetaMaps and MEGAN-LR. The test datasets were constructed with varying numbers of bacterial and eukaryotic genomes, to simulate different metagenomic applications. The tools were tested on their ability to accurately detect species and precisely estimate species abundances in the samples. Our analysis showed that all tested classifiers provide useful results, and that accuracy was strongly influenced by the comprehensiveness of the default database used. Using the same database for all tools provided comparable results across methods except for MetaMaps which had slightly better performance, but was slower than k-mer based tools.

Metagenomics ; long read sequencing ; taxonomic classification

nije evidentirano