ArticlePloS one2015
CoMeta: classification of metagenomes using k-mers.
Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed, 30 citations in OpenAlex.
- KnvResGAT: SARS-CoV-2 sequence classification using k-mer natural vector and graph attention networks.BMC research notes · 2026Article
- Classification ofiScience · 2024Article
- Strain level microbial detection and quantification with applications to single cell metagenomics.Nature communications · 2022Article
- PWM2Vec: An Efficient Embedding Approach for Viral Host Specification from Coronavirus Spike Sequences.Biology · 2022Article
- Music of metagenomics-a review of its applications, analysis pipeline, and associated tools.Functional & integrative genomics · 2022Review
- A Randomized Parallel Algorithm for Efficiently Finding Near-Optimal Universal Hitting Sets.Research in computational molecular biology : ... Annual International Conference, RECOMB ... : proceedings. RECOMB (Conference : 2005- ) · 2020Article
- Environmental metagenome classification for constructing a microbiome fingerprint.Biology direct · 2019Article
- DisCVR: Rapid viral diagnosis from high-throughput sequencing data.Virus evolution · 2019Article
- MicroPheno: predicting environments and host phenotypes from 16S rRNA gene sequencing using a k-mer based representation of shallow sub-samples.Bioinformatics (Oxford, England) · 2018Article
- Asymptotically optimal minimizers schemes.Bioinformatics (Oxford, England) · 2018Article
- MiR-218 targets MeCP2 and inhibits heroin seeking behavior.Scientific reports · 2017Article
- HostPhinder: A Phage Host Prediction Tool.Viruses · 2016Article
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Nowadays, the study of environmental samples has been developing rapidly. Characterization of the environment composition broadens the knowledge about the relationship between species composition and environmental conditions. An important element of extracting the knowledge of the sample composition is to compare the extracted fragments of DNA with sequences derived from known organisms. In the presented paper, we introduce an algorithm called CoMeta (Classification of metagenomes), which assigns a query read (a DNA fragment) into one of the groups previously prepared by the user. Typically, this is one of the taxonomic rank (e.g., phylum, genus), however prepared groups may contain sequences having various functions. In CoMeta, we used the exact method for read classification using short subsequences (k-mers) and fast program for indexing large set of k-mers. In contrast to the most popular methods based on BLAST, where the query is compared with each reference sequence, we begin the classification from the top of the taxonomy tree to reduce the number of comparisons. The presented experimental study confirms that CoMeta outperforms other programs used in this context. CoMeta is available at https://github.com/jkawulok/cometa under a free GNU GPL 2 license.
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Registered trials
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.