MetaQUAST: evaluation of metagenome assemblies

Mikheenko, Alla; Saveliev, Vladislav; Gurevich, Alexey

doi:10.1093/bioinformatics/btv697

Cited by 516 publications

(426 citation statements)

References 29 publications

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“…Quality trimmed forward and reverse sequences were merged and assembled into contigs using SPAdes 3.7.0 (Nurk et al, 2013) with the "-meta" option. The number of contigs, contig length, GC content, N50, and L50 assembly statistics were calculated with metaQUAST (Mikheenko et al, 2016;Supplementary Table 2). Contigs ≥ 500 bp were organized into genome bins based on tetranucleotide frequency and sequence coverage using MaxBin 2.0 .…”

Section: Metagenomic Analysismentioning

confidence: 99%

Metagenomic Binning Recovers a Transcriptionally Active Gammaproteobacterium Linking Methanotrophy to Partial Denitrification in an Anoxic Oxygen Minimum Zone

et al. 2017

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Diverse planktonic microorganisms play a crucial role in mediating methane flux from the ocean to the atmosphere. The distribution and composition of the marine methanotroph community is determined partly by oxygen availability. The low oxygen conditions of oxygen minimum zones (OMZs) may select for methanotrophs that oxidize methane using inorganic nitrogen compounds (e.g., nitrate, nitrite) in place of oxygen. However, environmental evidence for methane-nitrogen linkages in OMZs remains sparse, as does our knowledge of the genomic content and metabolic capacity of organisms catalyzing OMZ methane oxidation. Here, binning of metagenome sequences from a coastal anoxic OMZ recovered the first near complete (95%) draft genome representing the methanotroph clade OPU3. Phylogenetic reconstruction of concatenated single copy marker genes confirmed the OPU3-like bacterium as a divergent member of the type Ia methanotrophs, with an estimated genome size half that of other sequenced taxa in this group. The proportional abundance of this bacterium peaked at 4% of the total microbial community at the top of the anoxic zone in areas of nitrite and nitrate availability but low methane concentrations. Genes mediating dissimilatory nitrate and nitrite reduction were identified in the OPU3 genome, and transcribed in conjunction with key enzymes catalyzing methane oxidation to formaldehyde and the ribulose monophosphate (RuMP) pathway for formaldehyde assimilation, suggesting partial denitrification linked to methane oxidation. Together, these data provide the first field-based evidence for methanotrophic partial denitrification by the OPU3 cluster under anoxic conditions, supporting a role for OMZs as key sites in pelagic methane turnover.

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Section: Metagenomic Analysismentioning

confidence: 99%

Metagenomic Binning Recovers a Transcriptionally Active Gammaproteobacterium Linking Methanotrophy to Partial Denitrification in an Anoxic Oxygen Minimum Zone

et al. 2017

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“…Benchmarking various computational tools in genomics would not be possible without the development of specialized quality assessment tools aimed at various applications. For example, benchmarking of assembly tools would not be possible without the development of such tools for evaluating genomics (QUAST in (30)), metagenomics ( meta QUAST in (31)), and transcriptomics ( rna QUAST in (32)) assemblies. Similarly to other areas of genomics, developing a benchmarking framework for repertoire reconstructions is a pre-requisite for objective evaluation of the state-of-art immunoinformatics algorithms.…”

Section: Introductionmentioning

confidence: 99%

Reconstructing Antibody Repertoires from Error-Prone Immunosequencing Reads

Shlemov

Bankevich

Bzikadze

et al. 2017

The Journal of Immunology

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Transforming error-prone immunosequencing datasets into antibody repertoires is a fundamental problem in immunogenomics, and a prerequisite for studies of immune responses. Although various repertoire reconstruction algorithms were released in the last three years, it remains unclear how to benchmark them and how to assess the accuracy of the reconstructed repertoires. We describe an accurate IgReC algorithm for constructing antibody repertoires from high-throughput immunosequencing datasets and a new framework for assessing the quality of reconstructed repertoires. Surprisingly, antibody repertoires constructed by IgReC from barcoded immunosequencing datasets in the blind mode (without using information about unique molecular identifiers) improved upon the repertoires constructed by the state-of-the-art tools that use barcoding. This finding suggests that IgReC may alleviate the need to generate repertoires using the barcoding technology (the workhorse of current immunogenomics efforts) because our computational approach to error correction of immunosequencing data is nearly as powerful as the experimental approach based on barcoding.

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“…Contigs from the IMP-based iterative co-assembly undergo quality assessment as well as taxonomic annotation [54] followed by gene prediction and functional annotation [55] (Fig. 1 and section “Annotation and assembly quality assessment”).…”

Section: Resultsmentioning

confidence: 99%

“…The assemblies were assessed based on contiguity (N50 length), data usage (MG and MT reads mapped), and output volume (number of contigs above 1 kb and number of genes; Additional file 2: Table S5). Only the SM dataset allowed for ground truth-based assessment by means of aligning the generated de novo assembly contigs to the original 73 bacterial genomes used to simulate the data set (section “Simulated coupled metagenomic and metatranscriptomic dataset”) [12, 54]. This allowed the comparison of two additional quality metrics, i.e., the recovered genome fraction and the composite performance metric (CPM) proposed by Deng et al [62].…”

Section: Resultsmentioning

confidence: 99%

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IMP: a pipeline for reproducible reference-independent integrated metagenomic and metatranscriptomic analyses

Narayanasamy¹,

Jarosz²,

et al. 2016

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Existing workflows for the analysis of multi-omic microbiome datasets are lab-specific and often result in sub-optimal data usage. Here we present IMP, a reproducible and modular pipeline for the integrated and reference-independent analysis of coupled metagenomic and metatranscriptomic data. IMP incorporates robust read preprocessing, iterative co-assembly, analyses of microbial community structure and function, automated binning, as well as genomic signature-based visualizations. The IMP-based data integration strategy enhances data usage, output volume, and output quality as demonstrated using relevant use-cases. Finally, IMP is encapsulated within a user-friendly implementation using Python and Docker. IMP is available at http://r3lab.uni.lu/web/imp/ (MIT license).Electronic supplementary materialThe online version of this article (doi:10.1186/s13059-016-1116-8) contains supplementary material, which is available to authorized users.

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MetaQUAST: evaluation of metagenome assemblies

Abstract: Supplementary data are available at Bioinformatics online.

Cited by 516 publications

References 29 publications

Metagenomic Binning Recovers a Transcriptionally Active Gammaproteobacterium Linking Methanotrophy to Partial Denitrification in an Anoxic Oxygen Minimum Zone

Metagenomic Binning Recovers a Transcriptionally Active Gammaproteobacterium Linking Methanotrophy to Partial Denitrification in an Anoxic Oxygen Minimum Zone

Reconstructing Antibody Repertoires from Error-Prone Immunosequencing Reads

IMP: a pipeline for reproducible reference-independent integrated metagenomic and metatranscriptomic analyses

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