ArticlePloS one2014
WGSQuikr: fast whole-genome shotgun metagenomic classification.
Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed.
- A survey of k-mer methods and applications in bioinformatics.Computational and structural biotechnology journal · 2024Review
- TAMPA: interpretable analysis and visualization of metagenomics-based taxon abundance profiles.GigaScience · 2022Article
- Music of metagenomics-a review of its applications, analysis pipeline, and associated tools.Functional & integrative genomics · 2022Review
- Extreme Compressed Sensing of Poisson Rates from Multiple Measurements.IEEE transactions on signal processing : a publication of the IEEE Signal Processing Society · 2022Article
- Phylogenetic double placement of mixed samples.Bioinformatics (Oxford, England) · 2020Article
- To Petabytes and beyond: recent advances in probabilistic and signal processing algorithms and their application to metagenomics.Nucleic acids research · 2020Article
- MSC: a metagenomic sequence classification algorithm.Bioinformatics (Oxford, England) · 2019Article
- Approximate kernel reconstruction for time-varying networks.BioData mining · 2019Article
- Opportunities and obstacles for deep learning in biology and medicine.Journal of the Royal Society, Interface · 2018Review
- MetaGen: reference-free learning with multiple metagenomic samples.Genome biology · 2017Article
- A clinician's guide to microbiome analysis.Nature reviews. Gastroenterology & hepatology · 2017Review
- MetaShot: an accurate workflow for taxon classification of host-associated microbiome from shotgun metagenomic data.Bioinformatics (Oxford, England) · 2017Article
- Article
- Large-scale machine learning for metagenomics sequence classification.Bioinformatics (Oxford, England) · 2016Article
- CLARK: fast and accurate classification of metagenomic and genomic sequences using discriminative k-mers.BMC genomics · 2015Article
- ARK: Aggregation of Reads by K-Means for Estimation of Bacterial Community Composition.PloS one · 2015Article
- Metagenomics: tools and insights for analyzing next-generation sequencing data derived from biodiversity studies.Bioinformatics and biology insights · 2015Review
- Article
- Article
- MetaPalette: amSystemsArticle
Corrections and comments
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Authors and funding
3 authors.
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Abstract
With the decrease in cost and increase in output of whole-genome shotgun technologies, many metagenomic studies are utilizing this approach in lieu of the more traditional 16S rRNA amplicon technique. Due to the large number of relatively short reads output from whole-genome shotgun technologies, there is a need for fast and accurate short-read OTU classifiers. While there are relatively fast and accurate algorithms available, such as MetaPhlAn, MetaPhyler, PhyloPythiaS, and PhymmBL, these algorithms still classify samples in a read-by-read fashion and so execution times can range from hours to days on large datasets. We introduce WGSQuikr, a reconstruction method which can compute a vector of taxonomic assignments and their proportions in the sample with remarkable speed and accuracy. We demonstrate on simulated data that WGSQuikr is typically more accurate and up to an order of magnitude faster than the aforementioned classification algorithms. We also verify the utility of WGSQuikr on real biological data in the form of a mock community. WGSQuikr is a Whole-Genome Shotgun QUadratic, Iterative, K-mer based Reconstruction method which extends the previously introduced 16S rRNA-based algorithm Quikr. A MATLAB implementation of WGSQuikr is available at: http://sourceforge.net/projects/wgsquikr.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.