An Exact Matching Method for 16S rRNA Taxonomy Classification

One popular approach to taxonomy classification in the microbiome utilizes 16S ribosomal RNA sequences. The main challenge is that 16S rRNA sequences could be almost identical in closely related species, and it is difficult to distinguish them at the species level. Recent approaches are able to achi...

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Published inJournal of computational biology Vol. 32; no. 8; pp. 753 - 760
Main Author Sze, Sing-Hoi
Format Journal Article
LanguageEnglish
Published United States Mary Ann Liebert, Inc., publishers 01.08.2025
Subjects
Algorithms
Bacteria - classification
Bacteria - genetics
Computational Biology - methods
Humans
Microbiota - genetics
Phylogeny
Preface
RNA, Ribosomal, 16S - classification
RNA, Ribosomal, 16S - genetics
Software
16S rRNA
microbiome
taxonomy classification
Online AccessGet full text
ISSN1557-8666
1557-8666
DOI10.1089/cmb.2024.0615

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Abstract One popular approach to taxonomy classification in the microbiome utilizes 16S ribosomal RNA sequences. The main challenge is that 16S rRNA sequences could be almost identical in closely related species, and it is difficult to distinguish them at the species level. Recent approaches are able to achieve almost single nucleotide resolution by constructing an error model of the reads. We develop an exact matching algorithm to utilize the single nucleotide resolution directly. We show that our algorithm is able to obtain improved accuracy in recent samples of mock communities and in samples of high compositional complexity when compared to existing algorithms. A software program implementing this algorithm is available at http://faculty.cse.tamu.edu/shsze/kmpmatch .
AbstractList One popular approach to taxonomy classification in the microbiome utilizes 16S ribosomal RNA sequences. The main challenge is that 16S rRNA sequences could be almost identical in closely related species, and it is difficult to distinguish them at the species level. Recent approaches are able to achieve almost single nucleotide resolution by constructing an error model of the reads. We develop an exact matching algorithm to utilize the single nucleotide resolution directly. We show that our algorithm is able to obtain improved accuracy in recent samples of mock communities and in samples of high compositional complexity when compared to existing algorithms. A software program implementing this algorithm is available at http://faculty.cse.tamu.edu/shsze/kmpmatch .
One popular approach to taxonomy classification in the microbiome utilizes 16S ribosomal RNA sequences. The main challenge is that 16S rRNA sequences could be almost identical in closely related species, and it is difficult to distinguish them at the species level. Recent approaches are able to achieve almost single nucleotide resolution by constructing an error model of the reads. We develop an exact matching algorithm to utilize the single nucleotide resolution directly. We show that our algorithm is able to obtain improved accuracy in recent samples of mock communities and in samples of high compositional complexity when compared to existing algorithms. A software program implementing this algorithm is available at http://faculty.cse.tamu.edu/shsze/kmpmatch.One popular approach to taxonomy classification in the microbiome utilizes 16S ribosomal RNA sequences. The main challenge is that 16S rRNA sequences could be almost identical in closely related species, and it is difficult to distinguish them at the species level. Recent approaches are able to achieve almost single nucleotide resolution by constructing an error model of the reads. We develop an exact matching algorithm to utilize the single nucleotide resolution directly. We show that our algorithm is able to obtain improved accuracy in recent samples of mock communities and in samples of high compositional complexity when compared to existing algorithms. A software program implementing this algorithm is available at http://faculty.cse.tamu.edu/shsze/kmpmatch.
One popular approach to taxonomy classification in the microbiome utilizes 16S ribosomal RNA sequences. The main challenge is that 16S rRNA sequences could be almost identical in closely related species, and it is difficult to distinguish them at the species level. Recent approaches are able to achieve almost single nucleotide resolution by constructing an error model of the reads. We develop an exact matching algorithm to utilize the single nucleotide resolution directly. We show that our algorithm is able to obtain improved accuracy in recent samples of mock communities and in samples of high compositional complexity when compared to existing algorithms. A software program implementing this algorithm is available at http://faculty.cse.tamu.edu/shsze/kmpmatch.
Author Sze, Sing-Hoi
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Cites_doi 10.1128/mSystems.00062-16
10.1038/s41587-019-0209-9
10.1128/mSystems.00191-16
10.1093/nar/gkm864
10.1093/nar/gkv180
10.1093/nar/19.suppl.2017
10.1038/nmeth.f.303
10.1186/s12864-015-1419-2
10.1016/S0022-2836(05)80360-2
10.1128/mSphere.01202-20
10.1128/AEM.03006-05
10.1038/nmeth.3869
10.1093/bioinformatics/btq619
10.1186/gb-2014-15-3-r46
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SubjectTerms Algorithms
Bacteria - classification
Bacteria - genetics
Computational Biology - methods
Humans
Microbiota - genetics
Phylogeny
Preface
RNA, Ribosomal, 16S - classification
RNA, Ribosomal, 16S - genetics
Software
Title An Exact Matching Method for 16S rRNA Taxonomy Classification
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https://www.ncbi.nlm.nih.gov/pubmed/40485285
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