Culman Steven W, Bukowski Robert, Gauch Hugh G, Cadillo-Quiroz Hinsby, Buckley Daniel H
Department of Crop and Soil Sciences, Cornell University, Ithaca, NY, USA.
BMC Bioinformatics. 2009 Jun 6;10:171. doi: 10.1186/1471-2105-10-171.
Despite increasing popularity and improvements in terminal restriction fragment length polymorphism (T-RFLP) and other microbial community fingerprinting techniques, there are still numerous obstacles that hamper the analysis of these datasets. Many steps are required to process raw data into a format ready for analysis and interpretation. These steps can be time-intensive, error-prone, and can introduce unwanted variability into the analysis. Accordingly, we developed T-REX, free, online software for the processing and analysis of T-RFLP data.
Analysis of T-RFLP data generated from a multiple-factorial study was performed with T-REX. With this software, we were able to i) label raw data with attributes related to the experimental design of the samples, ii) determine a baseline threshold for identification of true peaks over noise, iii) align terminal restriction fragments (T-RFs) in all samples (i.e., bin T-RFs), iv) construct a two-way data matrix from labeled data and process the matrix in a variety of ways, v) produce several measures of data matrix complexity, including the distribution of variance between main and interaction effects and sample heterogeneity, and vi) analyze a data matrix with the additive main effects and multiplicative interaction (AMMI) model.
T-REX provides a free, platform-independent tool to the research community that allows for an integrated, rapid, and more robust analysis of T-RFLP data.
尽管末端限制性片段长度多态性（T-RFLP）及其他微生物群落指纹识别技术越来越受欢迎且有所改进，但仍存在许多阻碍这些数据集分析的障碍。将原始数据处理成可供分析和解读的格式需要许多步骤。这些步骤可能耗时、易出错，并且会在分析中引入不必要的变异性。因此，我们开发了T-REX，一款用于处理和分析T-RFLP数据的免费在线软件。
使用T-REX对多因素研究产生的T-RFLP数据进行了分析。通过该软件，我们能够：i）用与样本实验设计相关的属性标记原始数据；ii）确定识别真实峰高于噪声的基线阈值；iii）比对所有样本中的末端限制性片段（T-RF）（即对T-RF进行归类）；iv）根据标记数据构建双向数据矩阵，并以多种方式处理该矩阵；v）生成数据矩阵复杂性的多种度量，包括主效应和交互效应之间的方差分布以及样本异质性；vi）使用加性主效应和乘性交互作用（AMMI）模型分析数据矩阵。
T-REX为研究群体提供了一个免费的、独立于平台的工具，可对T-RFLP数据进行综合、快速且更稳健的分析。
