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:

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

Paired Two Conditions Data
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).

Multiple Conditions Data
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).

Downloads

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

Example Datasets
Download and explore different example high-throughput datasets.

Citing Cyber-T

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

P. Baldi and A.D. Long, "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).