<it>T-REX</it>: software for the processing and analysis of T-RFLP data

• Main Authors: Culman Steven W, Bukowski Robert, Gauch Hugh G, Cadillo-Quiroz Hinsby, Buckley Daniel H
• Format: Article
• Language: English
• Published: BMC 2009-06-01
• Series: BMC Bioinformatics
• Online Access: http://www.biomedcentral.com/1471-2105/10/171

<p>Abstract</p> <p>Background</p> <p>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 <it>T-REX</it>, free, online software for the processing and analysis of T-RFLP data.</p> <p>Results</p> <p>Analysis of T-RFLP data generated from a multiple-factorial study was performed with <it>T-REX</it>. 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.</p> <p>Conclusion</p> <p><it>T-REX </it>provides a free, platform-independent tool to the research community that allows for an integrated, rapid, and more robust analysis of T-RFLP data.</p>