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Bioinformatics Advance Access originally published online on March 30, 2006
Bioinformatics 2006 22(10):1272-1274; doi:10.1093/bioinformatics/btl108
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© The Author 2006. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

SScore: an R package for detecting differential gene expression without gene expression summaries

Richard E. Kennedy 1,*, Robnet T. Kerns 2, Xiangrong Kong 1, Kellie J. Archer 1,4 and Michael F. Miles 2,3,4

1 Department of Biostatistics, Virginia Commonwealth University Box 980032, Richmond, VA 23298-0032, USA
2 Department of Pharmacology and Toxicology, Virginia Commonwealth University Box 980032, Richmond, VA 23298-0032, USA
3 Department of Neurology, Virginia Commonwealth University Box 980032, Richmond, VA 23298-0032, USA
4 Center for the Study of Biological Complexity, Virginia Commonwealth University Box 980032, Richmond, VA 23298-0032, USA

*To whom correspondence should be addressed.

Summary: SScore is an R package that facilitates the comparison of gene expression between Affymetrix GeneChips using the S-score algorithm. The S-score algorithm uses probe level data directly to assess differences in gene expression, without requiring a preliminary separate step of probe set expression summary estimation. Therefore, the algorithm avoids introduction of error associated with the expression summary estimation process and has been demonstrated to improve the accuracy of identifying differentially expressed genes. The S-score produces accurate results even when few or no replicates are available.

Availability: The R package SScore is available from Bioconductor at http://www.bioconductor.org

Contact: rkennedy{at}vcu.edu

Received on December 5, 2005; revised on February 24, 2006; accepted on March 18, 2006

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