Ishii Satoshi, Kadota Koji, Senoo Keishi
Department of Applied Biological Chemistry, Graduate School of Agricultural and Life Sciences, The University of Tokyo, Japan.
J Microbiol Methods. 2009 Sep;78(3):344-50. doi: 10.1016/j.mimet.2009.07.005. Epub 2009 Jul 17.
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.
诸如扩增核糖体DNA限制性分析（ARDRA）、重复外显子回文PCR（rep-PCR）、核糖体基因间隔区分析（RISA）和变性梯度凝胶电泳（DGGE）等DNA指纹分析在微生物学的各个领域中经常被使用。DNA指纹数据分析的主要困难在于多个峰集的比对。我们在此报告一个基于聚类的峰比对算法的R程序，及其在分析各种DNA指纹数据（如ARDRA、rep-PCR、RISA和DGGE数据）中的应用。我们的聚类算法和BioNumerics软件获得的结果显示出高度相似性。由于已经建立了几个用于对各种生物学数据进行统计分析的R包，我们的R程序获得的距离矩阵可用于后续的统计分析，其中一些分析以前没有进行过，但在DNA指纹研究中很有用。
