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Cyber-T web server: differential analysis of high-throughput data.

Matthew A Kayala1, Pierre Baldi

  • 1Department of Computer Science and Institute for Genomics and Bioinformatics, University of California, Irvine, CA 92697, USA.

Nucleic Acids Research
|May 19, 2012
PubMed
Summary

The updated Cyber-T web server enhances high-throughput differential analysis using Bayesian regularization. It now offers improved normalization, ANOVA, and multiple testing corrections for gene expression studies.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Statistical Genomics

Background:

  • The Bayesian regularization method, implemented in Cyber-T, is a validated approach for high-throughput differential analysis.
  • It addresses challenges in microarray and other high-throughput data, such as low replication and technology biases.

Purpose of the Study:

  • To present an updated version of the Cyber-T web server with new features and improvements.
  • To enhance differential expression analysis for various high-throughput technologies.

Main Methods:

  • Incorporation of preprocessing data normalization options (logarithmic, Variance Stabilizing Normalization).
  • Implementation of one-way analysis of variance to augment two-sample t-tests.
  • Inclusion of multiple testing correction methods (frequentist, probabilistic mixture model).

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Main Results:

  • The updated Cyber-T server provides enhanced preprocessing and statistical analysis capabilities.
  • Diagnostic plots are available for visual assessment of results.
  • Comprehensive documentation and example datasets are provided.

Conclusions:

  • The updated Cyber-T web server offers a more robust and versatile platform for differential expression analysis.
  • It supports a wider range of high-throughput data types and analytical needs.
  • The tool is publicly accessible with R source code and data sets.