DADA2: High-resolution sample inference from Illumina amplicon data

Nature Methods, Год журнала: 2016, Номер 13(7), С. 581 - 583

Опубликована: Май 23, 2016

Язык: Английский

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VSEARCH: a versatile open source tool for metagenomics

PeerJ, Год журнала: 2016, Номер 4, С. e2584 - e2584

Опубликована: Окт. 18, 2016

VSEARCH is an open source and free of charge multithreaded 64-bit tool for processing preparing metagenomics, genomics population nucleotide sequence data. It designed as alternative to the widely used USEARCH (Edgar, 2010) which code not publicly available, algorithm details are only rudimentarily described, a memory-confined 32-bit version freely available academic use.When searching sequences, uses fast heuristic based on words shared by query target sequences in order quickly identify similar strategy probably USEARCH. then performs optimal global alignment against potential using full dynamic programming instead seed-and-extend Pairwise alignments computed parallel vectorisation multiple threads.VSEARCH includes most commands analysing 7 several those 8, including (exact or alignment), clustering similarity (using length pre-sorting, abundance pre-sorting user-defined order), chimera detection (reference-based de novo), dereplication (full prefix), pairwise alignment, reverse complementation, sorting, subsampling. also FASTQ file processing, i.e., format detection, filtering, read quality statistics, merging paired reads. Furthermore, extends functionality with new improvements, shuffling, rereplication, masking low-complexity well-known DUST algorithm, choice among different definitions, conversion. here shown be more accurate than when performing searching, clustering, subsampling, while par paired-ends merging. slower but significantly faster paired-end reads dereplication. at https://github.com/torognes/vsearch under either BSD 2-clause license GNU General Public License 3.0.VSEARCH has been fast, full-fledged A open-source versatile analysis now metagenomics community.

Язык: Английский

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Exact sequence variants should replace operational taxonomic units in marker-gene data analysis

The ISME Journal, Год журнала: 2017, Номер 11(12), С. 2639 - 2643

Опубликована: Июль 21, 2017

Abstract Recent advances have made it possible to analyze high-throughput marker-gene sequencing data without resorting the customary construction of molecular operational taxonomic units (OTUs): clusters reads that differ by less than a fixed dissimilarity threshold. New methods control errors sufficiently such amplicon sequence variants (ASVs) can be resolved exactly, down level single-nucleotide differences over sequenced gene region. The benefits finer resolution are immediately apparent, and arguments for ASV focused on their improved resolution. Less obvious, but we believe more important, broad derive from status ASVs as consistent labels with intrinsic biological meaning identified independently reference database. Here discuss how these features grant combined advantages closed-reference OTUs—including computational costs scale linearly study size, simple merging between processed sets, forward prediction—and de novo accurate measurement diversity applicability communities lacking deep coverage in databases. We argue improvements reusability, reproducibility comprehensiveness great should replace OTUs standard unit analysis reporting.

Язык: Английский

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UNOISE2: improved error-correction for Illumina 16S and ITS amplicon sequencing

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2016, Номер unknown

Опубликована: Окт. 15, 2016

Abstract Amplicon sequencing of tags such as 16S and ITS ribosomal RNA is a popular method for investigating microbial populations. In experiments, sequence errors caused by PCR are difficult to distinguish from true biological variation. I describe UNOISE2, an updated version the UNOISE algorithm denoising (error-correcting) Illumina amplicon reads show that it has comparable or better accuracy than DADA2.

Язык: Английский

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Salt-responsive gut commensal modulates TH17 axis and disease

Nature, Год журнала: 2017, Номер 551(7682), С. 585 - 589

Опубликована: Ноя. 1, 2017

Язык: Английский

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The ecology of environmental DNA and implications for conservation genetics

Conservation Genetics, Год журнала: 2015, Номер 17(1), С. 1 - 17

Опубликована: Сен. 8, 2015

Environmental DNA (eDNA) refers to the genetic material that can be extracted from bulk environmental samples such as soil, water, and even air. The rapidly expanding study of eDNA has generated unprecedented ability detect species conduct analyses for conservation, management, research, particularly in scenarios where collection whole organisms is impractical or impossible. While number studies demonstrating successful detection increased recent years, less research explored "ecology" eDNA—myriad interactions between extraorganismal its environment—and influence on detection, quantification, analysis, application conservation research. Here, we outline a framework understanding ecology eDNA, including origin, state, transport, fate material. Using this framework, review synthesize findings diverse environments, taxa, fields highlight important concepts knowledge gaps application. Additionally, identify frontiers conservation-focused see most potential growth, use estimating population size, genomic via inclusion other indicator biomolecules RNA proteins, automated sample consideration an expanded array creative samples. We discuss how more complete integral advancing these maximizing future applications

Язык: Английский

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Bioconductor Workflow for Microbiome Data Analysis: from raw reads to community analyses

F1000Research, Год журнала: 2016, Номер 5, С. 1492 - 1492

Опубликована: Ноя. 2, 2016

High-throughput sequencing of PCR-amplified taxonomic markers (like the 16S rRNA gene) has enabled a new level analysis complex bacterial communities known as microbiomes. Many tools exist to quantify and compare abundance levels or OTU composition in different conditions. The reads have be denoised assigned closest taxa from reference database. Common approaches use notion 97% similarity normalize data by subsampling equalize library sizes. In this paper, we show that statistical models allow more accurate estimates. By providing complete workflow R, enable user do sophisticated downstream analyses, whether parametric nonparametric. We provide examples using R packages dada2, phyloseq, DESeq2, ggplot2 vegan filter, visualize test microbiome data. also supervised analyses random forests nonparametric testing community networks ggnetwork package.

Язык: Английский

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Bioconductor workflow for microbiome data analysis: from raw reads to community analyses

F1000Research, Год журнала: 2016, Номер 5, С. 1492 - 1492

Опубликована: Июнь 24, 2016

High-throughput sequencing of PCR-amplified taxonomic markers (like the 16S rRNA gene) has enabled a new level analysis complex bacterial communities known as microbiomes. Many tools exist to quantify and compare abundance levels or microbial composition in different conditions. The reads have be denoised assigned closest taxa from reference database. Common approaches use notion 97% similarity normalize data by subsampling equalize library sizes. In this paper, we show that statistical models allow more accurate estimates. By providing complete workflow R, enable user do sophisticated downstream analyses, including both parameteric nonparametric methods. We provide examples using R packages dada2, phyloseq, DESeq2, ggplot2 vegan filter, visualize test microbiome data. also supervised analyses random forests, partial least squares linear well testing community networks ggnetwork package.

Язык: Английский

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A practical guide to amplicon and metagenomic analysis of microbiome data

Protein & Cell, Год журнала: 2020, Номер 12(5), С. 315 - 330

Опубликована: Май 11, 2020

Abstract Advances in high-throughput sequencing (HTS) have fostered rapid developments the field of microbiome research, and massive datasets are now being generated. However, diversity software tools complexity analysis pipelines make it difficult to access this field. Here, we systematically summarize advantages limitations methods. Then, recommend specific for amplicon metagenomic analyses, describe commonly-used databases, help researchers select appropriate tools. Furthermore, introduce statistical visualization methods suitable analysis, including alpha- beta-diversity, taxonomic composition, difference comparisons, correlation, networks, machine learning, evolution, source tracing, common styles informed choices. Finally, a step-by-step reproducible guide is introduced. We hope review will allow carry out data more effectively quickly order efficiently mine biological significance behind data.

Язык: Английский

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Updating the 97% identity threshold for 16S ribosomal RNA OTUs

Bioinformatics, Год журнала: 2018, Номер 34(14), С. 2371 - 2375

Опубликована: Фев. 27, 2018

The 16S ribosomal RNA (rRNA) gene is widely used to survey microbial communities. Sequences are often clustered into Operational Taxonomic Units (OTUs) as proxies for species. canonical clustering threshold 97% identity, which was proposed in 1994 when few rRNA sequences were available, motivating a reassessment on current data.Using large set of high-quality from finished genomes, I assessed the correspondence OTUs species five representative algorithms using four accuracy metrics. All had comparable tuned given metric. Optimal identity thresholds ∼99% full-length and ∼100% V4 hypervariable region.Reference source code provided Supplementary Material.Supplementary data available at Bioinformatics online.

Язык: Английский

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