Abstract
Background: Pre-processing, including normalization of raw microarray data is crucial to microarray-related data analysis. It takes time and effort to build newly-developed algorithms into commercial software or locally developed systems. While most new algorithms emerge in the form of sharable R packages, it can be difficult for many biologists to apply them as soon as they are available. Currently, we rely on statisticians and experienced programmers to develop and implement code to access those R packages. Therefore, we need a robust procedure to quickly implement pre-processing methods as they appear. The newly emerging cloud computing concept has directed us toward a new way for providing an easily accessible service to the biologists without requiring them to have any programming knowledge in R. Results: Based on our earlier Java-based software tool JavaStat, we developed an internet based application prototype to upload data and carry out pre-processing applications that include normalization, statistical analyses and plots. More im-portantly, R packages, e. g., for newly-developed normalization methods, and GC-robust multichip algorithm (RMA) for exon arrays, can be easily incorporated into the system with limited inputs from a biologist or a programmer. The data are stored in the cloud and the R code runs on server. Conclusion: The newly emerged cloud computing concept provides us a new way to provide an easily accessible and up-to-date service to biologists, as evidenced by our JavaStat system to incorporate new pre-processing package as they ap-pear. Users can access the application with a newly incorporated module through the Web. We expect this and other simi-lar systems greatly decrease turn-around time, improve accessibility of newly developed R model for pre-processing algo-rithms.
Highlights
JavaStatJavaStat, a previously reported system written in Java [1], has a highly interactive statistical and modeling environment
The computation and data storage are completely done on the server, so it is not necessary to install R on client machines and no additional knowledge of R is required for clients
The JRIServer listens to requests from the client programs and accesses R installed on server
Summary
JavaStatJavaStat, a previously reported system written in Java [1], has a highly interactive statistical and modeling environment. The front-end is an interactive graphical user interface (GUI) for data analysis and dynamic visualization with data management capabilities. The back-end server uses R/Bio-conductor as a powerful computing engine to run complex statistical models and carry out various types of microarray analyses. The concept revolves around the use of RMI (Remote Method Invocation) to communicate front-end commands with a back-end Java server program (JRIServer), which in turn communicates with R using JRI (Java/R Interface). We rely on statisticians and experienced programmers to develop and implement code to access those R packages. The newly emerging cloud computing concept has directed us toward a new way for providing an accessible service to the biologists without requiring them to have any programming knowledge in R. constant contrasts pmonly.avgdiff mtp zations and analyses, and download results without much input from a biologist or a programmer. Similar system will greatly increase the accessibility of new algorithms in R.
Sign-in/Register to view highlights & summary 
Published Version (
Free)
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call