Title |
Tools for T-RFLP data analysis using Excel
|
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Published in |
BMC Bioinformatics, November 2014
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DOI | 10.1186/s12859-014-0361-7 |
Pubmed ID | |
Authors |
Nils Johan Fredriksson, Malte Hermansson, Britt-Marie Wilén |
Abstract |
Terminal restriction fragment length polymorphism (T-RFLP) analysis is a DNA-fingerprinting method that can be used for comparisons of the microbial community composition in a large number of samples. There is no consensus on how T-RFLP data should be treated and analyzed before comparisons between samples are made, and several different approaches have been proposed in the literature. The analysis of T-RFLP data can be cumbersome and time-consuming, and for large datasets manual data analysis is not feasible. The currently available tools for automated T-RFLP analysis, although valuable, offer little flexibility, and few, if any, options regarding what methods to use. To enable comparisons and combinations of different data treatment methods an analysis template and an extensive collection of macros for T-RFLP data analysis using Microsoft Excel were developed. |
X Demographics
Geographical breakdown
Country | Count | As % |
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United Kingdom | 2 | 17% |
Germany | 2 | 17% |
Saudi Arabia | 1 | 8% |
Sweden | 1 | 8% |
United States | 1 | 8% |
France | 1 | 8% |
Australia | 1 | 8% |
Unknown | 3 | 25% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 7 | 58% |
Scientists | 5 | 42% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Japan | 2 | 3% |
Malaysia | 1 | 2% |
Germany | 1 | 2% |
Sudan | 1 | 2% |
United States | 1 | 2% |
Unknown | 56 | 90% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 15 | 24% |
Researcher | 13 | 21% |
Student > Master | 11 | 18% |
Student > Bachelor | 5 | 8% |
Other | 3 | 5% |
Other | 9 | 15% |
Unknown | 6 | 10% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 33 | 53% |
Biochemistry, Genetics and Molecular Biology | 9 | 15% |
Environmental Science | 5 | 8% |
Engineering | 2 | 3% |
Immunology and Microbiology | 2 | 3% |
Other | 4 | 6% |
Unknown | 7 | 11% |