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$299

Plugin

Bootstrapped ROC (bROC)

bROC algorithm is used in the discovery of differentially expressed probes/genes in microarray and RNA-seq experiments.

bROC plugin deploys in CLC Main Workbench and CLC Genomics Workbench.

ROC (receiver operating characteristic) is a generally applicable, non-parametric procedure that provides insight into the discriminatory properties of data features for a binary classifier. However, the method is not efficient for gene expression experiments as they generally do not produce a sufficient number of samples. bROC overcomes that limitation by resampling (bootstrapping) the expression data to produce a large number of simulated measurements that preserve the statistical properties of the original data.

Thus, bROC can produce detailed curves of sensitivity (probability of true positive detection) vs. 1-specificity (probability of false positive detection) for all features of interest. CONF = 2 AUC - 1, where AUC is the area under ROC curve, is the primary statistics used for detection of regulated features (probes/genes).

Version 3 (August 2013) includes data normalization and graphical outputs.

Guides

Further Reading

Installation

The plugin is easily installed from within the Workbench:

  1. Click Plugins in the Toolbar
  2. Click the tab Download Plugins
  3. Select the plugin you wish to install
  4. Click the Download and Install button

Download from www.clcbio.com

Alternatively, you can download the plugin.

Workbench Download