Application of a clustering-based peak alignment algorithm to analyze various DNA fingerprinting data

Satoshi Ishii, Koji Kadota, Keishi Senoo

Research output: Contribution to journalArticlepeer-review

20 Scopus citations

Abstract

DNA fingerprinting analysis such as amplified ribosomal DNA restriction analysis (ARDRA), repetitive extragenic palindromic PCR (rep-PCR), ribosomal intergenic spacer analysis (RISA), and denaturing gradient gel electrophoresis (DGGE) are frequently used in various fields of microbiology. The major difficulty in DNA fingerprinting data analysis is the alignment of multiple peak sets. We report here an R program for a clustering-based peak alignment algorithm, and its application to analyze various DNA fingerprinting data, such as ARDRA, rep-PCR, RISA, and DGGE data. The results obtained by our clustering algorithm and by BioNumerics software showed high similarity. Since several R packages have been established to statistically analyze various biological data, the distance matrix obtained by our R program can be used for subsequent statistical analyses, some of which were not previously performed but are useful in DNA fingerprinting studies.

Original languageEnglish (US)
Pages (from-to)344-350
Number of pages7
JournalJournal of Microbiological Methods
Volume78
Issue number3
DOIs
StatePublished - Sep 2009
Externally publishedYes

Bibliographical note

Funding Information:
This work was supported by the Program for Promotion of Basic Research Activities for Innovative Biosciences (PROBRAIN) from Bio-oriented Technology Research Advancement Institution, Japan (to SI and KS). Additional financial support was provided by Special Coordination Funds for Promoting Science and Technology, and by a Grant-in-Aid for Scientific Research (No. 19700273 ) from Japan Society for the Promotion of Science (to KK) .

Keywords

  • Complete linkage clustering
  • DNA fingerprinting
  • Peak alignment
  • R program
  • Statistics

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