Dataset Information

TaxMaps: comprehensive and highly accurate taxonomic classification of short-read data in reasonable time.

ABSTRACT: High-throughput sequencing is a revolutionary technology for the analysis of metagenomic samples. However, querying large volumes of reads against comprehensive DNA/RNA databases in a sensitive manner can be compute-intensive. Here, we present taxMaps, a highly efficient, sensitive, and fully scalable taxonomic classification tool. Using a combination of simulated and real metagenomics data sets, we demonstrate that taxMaps is more sensitive and more precise than widely used taxonomic classifiers and is capable of delivering classification accuracy comparable to that of BLASTN, but at up to three orders of magnitude less computational cost.

SUBMITTER: Corvelo A

PROVIDER: S-EPMC5932614 | biostudies-literature | 2018 May

REPOSITORIES: biostudies-literature

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taxMaps: comprehensive and highly accurate taxonomic classification of short-read data in reasonable time.

Corvelo André A Clarke Wayne E WE Robine Nicolas N Zody Michael C MC

Genome research 20180327 5

High-throughput sequencing is a revolutionary technology for the analysis of metagenomic samples. However, querying large volumes of reads against comprehensive DNA/RNA databases in a sensitive manner can be compute-intensive. Here, we present taxMaps, a highly efficient, sensitive, and fully scalable taxonomic classification tool. Using a combination of simulated and real metagenomics data sets, we demonstrate that taxMaps is more sensitive and more precise than widely used taxonomic classifier ...[more]

PMID: 29588360

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Project description:Studying the evolution of viruses and their molecular epidemiology relies on accurate viral sequence data, so that small differences between similar viruses can be meaningfully interpreted. Despite its higher throughput and more detailed minority variant data, next-generation sequencing has yet to be widely adopted for HIV. The difficulty of accurately reconstructing the consensus sequence of a quasispecies from reads (short fragments of DNA) in the presence of large between- and within-host diversity, including frequent indels, may have presented a barrier. In particular, mapping (aligning) reads to a reference sequence leads to biased loss of information; this bias can distort epidemiological and evolutionary conclusions. De novo assembly avoids this bias by aligning the reads to themselves, producing a set of sequences called contigs. However contigs provide only a partial summary of the reads, misassembly may result in their having an incorrect structure, and no information is available at parts of the genome where contigs could not be assembled. To address these problems we developed the tool shiver to pre-process reads for quality and contamination, then map them to a reference tailored to the sample using corrected contigs supplemented with the user's choice of existing reference sequences. Run with two commands per sample, it can easily be used for large heterogeneous data sets. We used shiver to reconstruct the consensus sequence and minority variant information from paired-end short-read whole-genome data produced with the Illumina platform, for sixty-five existing publicly available samples and fifty new samples. We show the systematic superiority of mapping to shiver's constructed reference compared with mapping the same reads to the closest of 3,249 real references: median values of 13 bases called differently and more accurately, 0 bases called differently and less accurately, and 205 bases of missing sequence recovered. We also successfully applied shiver to whole-genome samples of Hepatitis C Virus and Respiratory Syncytial Virus. shiver is publicly available from https://github.com/ChrisHIV/shiver.

Dataset Information

TaxMaps: comprehensive and highly accurate taxonomic classification of short-read data in reasonable time.

Publications

taxMaps: comprehensive and highly accurate taxonomic classification of short-read data in reasonable time.

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