Title |
Performing statistical analyses on quantitative data in Taverna workflows: An example using R and maxdBrowse to identify differentially-expressed genes from microarray data
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Published in |
BMC Bioinformatics, August 2008
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DOI | 10.1186/1471-2105-9-334 |
Pubmed ID | |
Authors |
Peter Li, Juan I Castrillo, Giles Velarde, Ingo Wassink, Stian Soiland-Reyes, Stuart Owen, David Withers, Tom Oinn, Matthew R Pocock, Carole A Goble, Stephen G Oliver, Douglas B Kell |
Abstract |
There has been a dramatic increase in the amount of quantitative data derived from the measurement of changes at different levels of biological complexity during the post-genomic era. However, there are a number of issues associated with the use of computational tools employed for the analysis of such data. For example, computational tools such as R and MATLAB require prior knowledge of their programming languages in order to implement statistical analyses on data. Combining two or more tools in an analysis may also be problematic since data may have to be manually copied and pasted between separate user interfaces for each tool. Furthermore, this transfer of data may require a reconciliation step in order for there to be interoperability between computational tools. |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 4 | 5% |
Netherlands | 2 | 3% |
United States | 2 | 3% |
Cuba | 1 | 1% |
Hong Kong | 1 | 1% |
Australia | 1 | 1% |
Sweden | 1 | 1% |
Brazil | 1 | 1% |
Italy | 1 | 1% |
Other | 4 | 5% |
Unknown | 58 | 76% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 28 | 37% |
Student > Ph. D. Student | 12 | 16% |
Professor | 6 | 8% |
Other | 5 | 7% |
Professor > Associate Professor | 5 | 7% |
Other | 17 | 22% |
Unknown | 3 | 4% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 27 | 36% |
Computer Science | 20 | 26% |
Medicine and Dentistry | 4 | 5% |
Engineering | 4 | 5% |
Environmental Science | 3 | 4% |
Other | 10 | 13% |
Unknown | 8 | 11% |