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Bioinformatics Advance Access published online on March 30, 2006
Bioinformatics, 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
Received December 5, 2005
Revised February 24, 2006
Accepted March 18, 2006

Applications note

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 3, and Michael F. Miles 4

1 Department of Biostatistics, Virginia Commonwealth University
2 Department of Pharmacology and Toxicology, Virginia Commonwealth University
3 Department of Biostatistics, Virginia Commonwealth University; Center for the Study of Biological Complexity, Virginia Commonwealth University
4 Department of Pharmacology and Toxicology, Virginia Commonwealth University; Department of Neurology, Virginia Commonwealth University; Center for the Study of Biological Complexity, Virginia Commonwealth University

* To whom correspondence should be addressed.
Richard E. Kennedy, E-mail: rkennedy{at}hsc.vcu.edu


  Abstract

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.

Associate Editor: Joaquin Dopazo
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