Evidence map›Paper›PMID 19500385›Full record

ArticleBMC bioinformatics2009

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

Steven W Culman, Robert Bukowski, Hugh G Gauch, Hinsby Cadillo-Quiroz, Daniel H Buckley

Abstract read
In one paragraph

Article in BMC bioinformatics, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 104 papers.

0numbers the graph read from it
0cells of the map it votes in
104citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

104 citing papers in PubMed.

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  3. Phosphate fertilization affects rhizosphere microbiome of maize and sorghum genotypes.Brazilian journal of microbiology : [publication of the Brazilian Society for Microbiology] · 2022
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44 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Steven W CulmanDepartment of Crop and Soil Sciences, Cornell University, Ithaca, NY, USA. swculman@ucdavis.edu
Robert Bukowski
Hugh G Gauch
Hinsby Cadillo-Quiroz
Daniel H Buckley

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDespite 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.

resultsAnalysis 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.

conclusionT-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.

Indexed as

Polymorphism, Restriction Fragment LengthSoftwareAnalysis of VarianceDatabase Management SystemsDatabases, GeneticDNA FingerprintingGenes, BacterialInternetModels, StatisticalSequence AlignmentSequence Analysis, DNAUser-Computer Interface

Identifiers

PMID19500385
PMCPMC2702334

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.