tetano
Editor, Senior Moderator
Brief Bioinform
. 2020 Oct 1;bbaa231.
doi: 10.1093/bib/bbaa231. Online ahead of print.
A computational toolset for rapid identification of SARS-CoV-2, other viruses and microorganisms from sequencing data
Shifu Chen[SUP] 1 [/SUP], Changshou He[SUP] 2 [/SUP], Yingqiang Li[SUP] 2 [/SUP], Zhicheng Li[SUP] 3 [/SUP], Charles E Melan?on[SUP] 4 [/SUP]
Affiliations
Abstract
In this paper, we present a toolset and related resources for rapid identification of viruses and microorganisms from short-read or long-read sequencing data. We present fastv as an ultra-fast tool to detect microbial sequences present in sequencing data, identify target microorganisms and visualize coverage of microbial genomes. This tool is based on the k-mer mapping and extension method. K-mer sets are generated by UniqueKMER, another tool provided in this toolset. UniqueKMER can generate complete sets of unique k-mers for each genome within a large set of viral or microbial genomes. For convenience, unique k-mers for microorganisms and common viruses that afflict humans have been generated and are provided with the tools. As a lightweight tool, fastv accepts FASTQ data as input and directly outputs the results in both HTML and JSON formats. Prior to the k-mer analysis, fastv automatically performs adapter trimming, quality pruning, base correction and other preprocessing to ensure the accuracy of k-mer analysis. Specifically, fastv provides built-in support for rapid severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) identification and typing. Experimental results showed that fastv achieved 100% sensitivity and 100% specificity for detecting SARS-CoV-2 from sequencing data; and can distinguish SARS-CoV-2 from SARS, Middle East respiratory syndrome and other coronaviruses. This toolset is available at: https://github.com/OpenGene/fastv.
Keywords: SARS-CoV-2; identification; k-mer; microorganisms; viruses.
. 2020 Oct 1;bbaa231.
doi: 10.1093/bib/bbaa231. Online ahead of print.
A computational toolset for rapid identification of SARS-CoV-2, other viruses and microorganisms from sequencing data
Shifu Chen[SUP] 1 [/SUP], Changshou He[SUP] 2 [/SUP], Yingqiang Li[SUP] 2 [/SUP], Zhicheng Li[SUP] 3 [/SUP], Charles E Melan?on[SUP] 4 [/SUP]
Affiliations
- PMID: 33003197
- DOI: 10.1093/bib/bbaa231
Abstract
In this paper, we present a toolset and related resources for rapid identification of viruses and microorganisms from short-read or long-read sequencing data. We present fastv as an ultra-fast tool to detect microbial sequences present in sequencing data, identify target microorganisms and visualize coverage of microbial genomes. This tool is based on the k-mer mapping and extension method. K-mer sets are generated by UniqueKMER, another tool provided in this toolset. UniqueKMER can generate complete sets of unique k-mers for each genome within a large set of viral or microbial genomes. For convenience, unique k-mers for microorganisms and common viruses that afflict humans have been generated and are provided with the tools. As a lightweight tool, fastv accepts FASTQ data as input and directly outputs the results in both HTML and JSON formats. Prior to the k-mer analysis, fastv automatically performs adapter trimming, quality pruning, base correction and other preprocessing to ensure the accuracy of k-mer analysis. Specifically, fastv provides built-in support for rapid severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) identification and typing. Experimental results showed that fastv achieved 100% sensitivity and 100% specificity for detecting SARS-CoV-2 from sequencing data; and can distinguish SARS-CoV-2 from SARS, Middle East respiratory syndrome and other coronaviruses. This toolset is available at: https://github.com/OpenGene/fastv.
Keywords: SARS-CoV-2; identification; k-mer; microorganisms; viruses.