ArticleBMC bioinformatics2016
Scalable metagenomics alignment research tool (SMART): a scalable, rapid, and complete search heuristic for the classification of metagenomic sequences from complex sequence populations.
Article in BMC bioinformatics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed.
- Molecular and Clinical Characterization of Human Adenovirus E4-Associated Conjunctivitis.American journal of ophthalmology · 2022Trial
- Determinants of Outcomes of Adenoviral Keratoconjunctivitis.Ophthalmology · 2018Trial
- Association of Seasonal Hyperacute Panuveitis Syndrome withOphthalmology science · 2026Article
- Detection for New Biomarkers of Tuberculosis Infection Activity Using Machine Learning Methods.Diseases (Basel, Switzerland) · 2026Review
- Targeted long-read sequencing enriches disease-relevant genomic regions of interest to provide complete Mendelian disease diagnostics.JCI insight · 2024Article
- Reconstruction of the personal information from human genome reads in gut metagenome sequencing data.Nature microbiology · 2023Article
- Machine Learning Prediction of Adenovirus D8 Conjunctivitis Complications from Viral Whole-Genome Sequence.Ophthalmology science · 2022Article
- Deep Metagenomic Sequencing for Endophthalmitis Pathogen Detection Using a Nanopore Platform.American journal of ophthalmology · 2022Article
- PathoLive-Real-Time Pathogen Identification from Metagenomic Illumina Datasets.Life (Basel, Switzerland) · 2022Article
- Molecular Diagnostics for Ocular Infectious Diseases: LXXVIII Edward Jackson Memorial Lecture.American journal of ophthalmology · 2022Review
- Technology dictates algorithms: recent developments in read alignment.Genome biology · 2021Review
- Prognostic Utility of Whole-Genome Sequencing and Polymerase Chain Reaction Tests of Ocular Fluids in Postprocedural Endophthalmitis.American journal of ophthalmology · 2020Article
- Clinical metagenomics for infectious corneal ulcers: Rags to riches?The ocular surface · 2020Article
- Small Myristoylated Protein-3, Identified as a Potential Virulence Factor in Leishmania amazonensis, Proves to be a Protective Antigen against Visceral Leishmaniasis.International journal of molecular sciences · 2018Article
- A Computational Approach Using Bioinformatics to Screening Drug Targets forEvidence-based complementary and alternative medicine : eCAM · 2018Article
- Overview of Virus Metagenomic Classification Methods and Their Biological Applications.Frontiers in microbiology · 2018Review
- Identifying Corneal Infections in Formalin-Fixed Specimens Using Next Generation Sequencing.Investigative ophthalmology & visual science · 2018Article
- Evaluation of a hypothetical protein for serodiagnosis and as a potential marker for post-treatment serological evaluation of tegumentary leishmaniasis patients.Parasitology research · 2017Article
- Host-Microbiome Interaction and Cancer: Potential Application in Precision Medicine.Frontiers in physiology · 2016Review
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3 authors.
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Abstract
backgroundNext generation sequencing technology has enabled characterization of metagenomics through massively parallel genomic DNA sequencing. The complexity and diversity of environmental samples such as the human gut microflora, combined with the sustained exponential growth in sequencing capacity, has led to the challenge of identifying microbial organisms by DNA sequence. We sought to validate a Scalable Metagenomics Alignment Research Tool (SMART), a novel searching heuristic for shotgun metagenomics sequencing results.
resultsAfter retrieving all genomic DNA sequences from the NCBI GenBank, over 1 × 10(11) base pairs of 3.3 × 10(6) sequences from 9.25 × 10(5) species were indexed using 4 base pair hashtable shards. A MapReduce searching strategy was used to distribute the search workload in a computing cluster environment. In addition, a one base pair permutation algorithm was used to account for single nucleotide polymorphisms and sequencing errors. Simulated datasets used to evaluate Kraken, a similar metagenomics classification tool, were used to measure and compare precision and accuracy. Finally using a same set of training sequences we compared Kraken, CLARK, and SMART within the same computing environment. Utilizing 12 computational nodes, we completed the classification of all datasets in under 10 min each using exact matching with an average throughput of over 1.95 × 10(6) reads classified per minute. With permutation matching, we achieved sensitivity greater than 83 % and precision greater than 94 % with simulated datasets at the species classification level. We demonstrated the application of this technique applied to conjunctival and gut microbiome metagenomics sequencing results. In our head to head comparison, SMART and CLARK had similar accuracy gains over Kraken at the species classification level, but SMART required approximately half the amount of RAM of CLARK.
conclusionsSMART is the first scalable, efficient, and rapid metagenomics classification algorithm capable of matching against all the species and sequences present in the NCBI GenBank and allows for a single step classification of microorganisms as well as large plant, mammalian, or invertebrate genomes from which the metagenomic sample may have been derived.
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