Development and application of a T-RFLP data analysis method using correlation coefficient matrices
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Updated: Jul 1, 2026

CorrelationCalculator and Filigree: Tools for Data-Driven Network Analysis of Metabolomics Data
Published on: November 10, 2023
Yoshio Nakano1, Toru Takeshita, Noriaki Kamio
1Department of Preventive Dentistry, Faculty of Dental Science, Kyushu University, Fukuoka, Japan. yosh@dent.kyushu-u.ac.jp
Abstract:
Environmental microbiology studies commonly use terminal restriction fragment length polymorphism (T-RFLP) of 16S rRNA genes, for example, to analyze changes in community structure in relation to changing physicochemical and biological conditions over space and time. Although T-RFLP is most useful for comparing samples from different environments, a large number of samples makes effective analysis difficult using the Web-based tools that are currently available. To resolve this dilemma, we used a new approach for calculating data from multiple T-RFLP samples by estimating terminal fragment combinations, then applying a correlation analysis using two different fluorescent dyes generated simultaneously from all samples. This calculation was based on the expectation that the proportions of two terminal fragments from one full-length polymerase chain reaction fragment would be nearly the same in each analysis. Using this program, the oral microflora in 73 human saliva samples were analyzed, and 24 bacterial groups, with peak areas of at least 0.5% and correlation coefficients of 0.55 or greater, were identified from the T-RFs within 40 s.
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