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TUIT, a BLAST-based tool for taxonomic classification of nucleotide sequences

Overview of attention for article published in Biotechniques, April 2018
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Article details
Title
TUIT, a BLAST-based tool for taxonomic classification of nucleotide sequences
Published in
Biotechniques, April 2018
DOI 10.2144/000114135
Pubmed ID
Authors
Abstract

Pyrosequencing of 16S ribosomal RNA (rRNA) genes has become the gold standard in human microbiome studies. The routine task of taxonomic classification using 16S rRNA reads is commonly performed by the Ribosomal Database Project (RDP) II Classifier, a robust tool that relies on a set of well-characterized reference sequences. However, the RDP II Classifier may be unable to classify a significant part of the data set due to the absence of proper reference sequences. The taxonomic classification for some unclassified sequences might still be performed using BLAST searches against large and frequently updated nucleotide databases. Here we introduce TUIT (Taxonomic Unit Identification Tool)-an efficient open source and platform-independent application that can perform taxonomic classification on its own or can be used in combination with the RDP II Classifier to maximize the taxonomic identification rate. Using a set of simulated DNA sequences, we demonstrate that the algorithm performs taxonomic classification with high specificity for sequences as short as 125 base pairs. TUIT is applicable for 16S rRNA gene sequence classification; however, it is not restricted to 16S rRNA sequences. In addition, TUIT may be used as a complementary tool for effective taxonomic classification of nucleotide sequences generated by many current platforms, such as Roche 454 and Illumina. Stand-alone TUIT is available online at http://sourceforge.net/projects/tuit/.

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Mendeley demographics

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The data shown below were compiled from readership statistics for 109 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
Belgium 2 2%
United States 1 <1%
Sweden 1 <1%
India 1 <1%
United Kingdom 1 <1%
France 1 <1%
Spain 1 <1%
Estonia 1 <1%
Germany 1 <1%
Other 0 0%
Unknown 99 91%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Researcher 40 37%
Student > Ph. D. Student 22 20%
Student > Bachelor 6 6%
Student > Master 6 6%
Other 5 5%
Other 16 15%
Unknown 14 13%
Readers by discipline
Readers by discipline Count As %
Agricultural and Biological Sciences 55 50%
Biochemistry, Genetics and Molecular Biology 14 13%
Computer Science 6 6%
Medicine and Dentistry 6 6%
Environmental Science 5 5%
Other 6 6%
Unknown 17 16%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 09 February 2014.
All research outputs
#28,780,377
of 34,559,526 outputs
Outputs from Biotechniques
#3,683
of 3,853 outputs
Outputs of similar age
#301,792
of 372,223 outputs
Outputs of similar age from Biotechniques
#571
of 619 outputs
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