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BMC Bioinformatics. 2009 Jun 6;10:171. doi: 10.1186/1471-2105-10-171.

T-REX: software for the processing and analysis of T-RFLP data.

Author information

1
Department of Crop and Soil Sciences, Cornell University, Ithaca, NY, USA. swculman@ucdavis.edu

Abstract

BACKGROUND:

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.

RESULTS:

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.

CONCLUSION:

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.

PMID:
19500385
PMCID:
PMC2702334
DOI:
10.1186/1471-2105-10-171
[Indexed for MEDLINE]
Free PMC Article

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