RabbitV: fast detection of viruses and microorganisms in sequencing data on multi-core architectures.
Bioinformatics
; 2022 Mar 25.
Article
in English
| MEDLINE | ID: covidwho-1764501
ABSTRACT
MOTIVATION Detection and identification of viruses and microorganisms in sequencing data plays an important role in pathogen diagnosis and research. However, existing tools for this problem often suffer from high runtimes and memory consumption. RESULTS:
We present RabbitV, a tool for rapid detection of viruses and microorganisms in Illumina sequencing datasets based on fast identification of unique k-mers. It can exploit the power of modern multi-core CPUs by using multi-threading, vectorization, and fast data parsing. Experiments show that RabbitV outperforms fastv by a factor of at least 42.5 and 14.4 in unique k-mer generation (RabbitUniq) and pathogen identification (RabbitV), respectively. Furthermore, RabbitV is able to detect COVID-19 from 40 samples of sequencing data (255GB in FASTQ format) in only 320 seconds.AVAILABILITY:
RabbitUniq and RabbitV are available at https//github.com/RabbitBio/RabbitUniq and https//github.com/RabbitBio/RabbitV. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Language:
English
Journal subject:
Medical Informatics
Year:
2022
Document Type:
Article
Affiliation country:
Bioinformatics
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