RT Journal Article
SR Electronic
T1 kASA: Taxonomic Analysis of Metagenomic Data on a Notebook
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 713966
DO 10.1101/713966
A1 Silvio Weging
A1 Andreas Gogol-Döring
A1 Ivo Grosse
YR 2019
UL http://biorxiv.org/content/early/2019/09/10/713966.abstract
AB The taxonomic analysis of sequencing data has become important in many areas of life sciences. However, currently available software tools for that purpose either consume large amounts of RAM or yield an insufficient quality of the results.Here we present kASA, a k-mer based software capable of identifying and profiling metagenomic sequences with high computational efficiency and a small user-definable memory footprint. We ensure high sensitivity and precision via k-mers on amino acid level with a dynamic length of multiple k’s. Custom algorithms and data structures that are optimised for external memory storage enable for the first time a full-scale metagenomics analysis without compromise on a standard notebook.RAMRandom Access Memory,LCAleast-common-ancestor,SSDSolid State Drive,I/OIn- and Output,BWTBurrows-Wheeler transform,NGSNext Generation Sequencing,HPCCHigh Performance Computing Cluster