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deSPI: efficient classification of metagenomic reads with lightweight de Bruijn graph-based reference indexing
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Abstract
Summary
In metagenomic studies, fast and effective tools are on wide demand to implement taxonomy classification for upto billions of reads. Herein, we propose deSPI, a novel read classification method that classifies reads by recognizing and analyzing the matches between reads and reference with de Bruijn graph-based lightweight reference indexing. deSPI has faster speed with relatively small memory footprint, meanwhile, it can also achieve higher or similar sensitivity and accuracy.
Availability
the C++ source code of deSPI is available at
https://github.com/hitbc/deSPI
Contact
ydwang@hit.edu.cn
Supplementary information
Supplementary data are available at
Bioinformatics
online.
Title: deSPI: efficient classification of metagenomic reads with lightweight de Bruijn graph-based reference indexing
Description:
Abstract
Summary
In metagenomic studies, fast and effective tools are on wide demand to implement taxonomy classification for upto billions of reads.
Herein, we propose deSPI, a novel read classification method that classifies reads by recognizing and analyzing the matches between reads and reference with de Bruijn graph-based lightweight reference indexing.
deSPI has faster speed with relatively small memory footprint, meanwhile, it can also achieve higher or similar sensitivity and accuracy.
Availability
the C++ source code of deSPI is available at
https://github.
com/hitbc/deSPI
Contact
ydwang@hit.
edu.
cn
Supplementary information
Supplementary data are available at
Bioinformatics
online.
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