ParaSAM: a parallelized version of the significance analysis of microarrays algorithm.
BACKGROUND
Significance analysis of microarrays (SAM) is a widely used permutation-based approach to identifying differentially expressed genes in microarray datasets. While SAM is freely available as an Excel plug-in and as an R-package, analyses are often limited for large datasets due to very high memory requirements.


CONCLUSIONS
We have developed a parallelized version of the SAM algorithm called ParaSAM to overcome the memory limitations. This high performance multithreaded application provides the scientific community with an easy and manageable client-server Windows application with graphical user interface and does not require programming experience to run. The parallel nature of the application comes from the use of web services to perform the permutations. Our results indicate that ParaSAM is not only faster than the serial version, but also can analyze extremely large datasets that cannot be performed using existing implementations.


BACKGROUND
A web version open to the public is available at http://bioanalysis.genomics.mcg.edu/parasam. For local installations, both the windows and web implementations of ParaSAM are available for free at http://www.amdcc.org/bioinformatics/software/parasam.aspx.
Sharma
Ashok
A
Center for Biotechnology and Genomic Medicine, School of Medicine, Medical College of Georgia, Augusta, GA 30912, USA.
Zhao
Jieping
J
Podolsky
Robert
R
McIndoe
Richard A
RA
D000465:Algorithms; D016208:Databases, Factual; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D012984:Software
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