![]() In the dialog box, add the following information about your toolbox. In the Package a Toolbox dialog box, click the button and select your toolbox folder. Using routines from Statistics and Machine Learning Toolbox, you can classify your results, perform hierarchical and K-means clustering, and represent your microarray data in statistical visualizations, such as 2D clustergrams with optimal leaf ordering, heat maps, principle component plots, and classification trees. How do I create a custom toolbox in Matlab To create a toolbox installation file: In the Environment section of the Home tab, select Package Toolbox from the Add-Ons menu. You can also visualize ideograms with G-banding patterns. Specialized routines for visualizing microarray data include volcano plots, box plots, loglog plots, I-R plots, and spatial heat maps of the microarray. You can also perform rank-invariant set normalization on either probe intensities for multiple Affymetrix CEL files or gene expression values from two different experimental conditions. You can apply circular binary segmentation to array CGH data and estimate the false discovery rate of multiple hypotheses testing of gene expression data from a microarray experiment.
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