Cyber-T provides differential analysis tools for high-throughput data. The system handles many types of data, from DNA and Protein microarrays, to Next Generation Sequencing, to Quantitative Mass Spectrometry.

Getting Started

Click on the link below corresponding to the type of data you would like to analyze:

Data from unpaired experiments, e.g., separate control and experimental samples.
(Standard t-test and Bayes-regularized t-test).

Data from paired experiments, e.g., before treatment vs. after treatment on the same biological samples.
(Paired t-test and Bayes-regularized paired t-test).

Data from experiments with more than two conditions, e.g., treatment A, treatment B, and treatment C
(One-way ANOVA and Bayes-regularized one-way ANOVA).


Download the R source code to run Cyber-T on your own computer.

Download and explore different example high-throughput datasets.

Citing Cyber-T

Please cite the following papers when you use Cyber-T in your work:

Kayala, M.A. and Baldi, P., "Cyber-T web server: differential analysis of high-throughput data", Nucleic Acids Research, 40 (W1): W553-W559, (2012). [Pubmed]

Baldi, P. and Long, A.D., "A Bayesian Framework for the Analysis of Microarray Expression Data: Regularized t-Test and Statistical Inferences of Gene Changes", Bioinformatics, 17, 6, 509-519, (2001). [Pubmed]