Computational Bioinformatics & Bioimaging Laboratory caBIG-ICR - VISDA VT –GU Developer Team: Huai Li, Jiajing Wang, Yue Wang, Jianhua Xuan, Robert Clarke.

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Computational Bioinformatics & Bioimaging Laboratory caBIG-ICR - VISDA VT –GU Developer Team: Huai Li, Jiajing Wang, Yue Wang, Jianhua Xuan, Robert Clarke UPenn – The Wistar Institute Adopter Team: Louise Showe, Michael Showe, Malik Yousef, Hsiuan-Lin Wu, and Michael Nebozhyn

Computational Bioinformatics & Bioimaging Laboratory Model clustered data structure via hierarchical mixture of Gaussian kernels (adaptive with cluster validation) Visualize data clusters via discriminative projections incorporating human gift for pattern recognition Discover and display hidden data clusters via top- down “soft” clustering (hierarchical yet exploratory) (VIsual Statistical Data Analyzer)is a caBIG -TM analytical tool for cluster modeling, visualization, and discovery VISDA (VIsual Statistical Data Analyzer) is a caBIG -TM analytical tool for cluster modeling, visualization, and discovery VISDA Overview

Computational Bioinformatics & Bioimaging Laboratory VISDA-caBIG TM Key Features Supported Data File –Support data retrieving from caArray –Support local MAGE-ML file format –Support tab-delimited data file with multiple gene annotations as well as multiple sample annotations Analytical Algorithms –Support sample clustering and gene clustering –Has supervised/unsupervised feature selection –Has PCA and PPM projections –Has hierarchical statistical modeling and parameter estimation by EM algorithm –Has advanced options for DCA projection and MDL cluster validation

Computational Bioinformatics & Bioimaging Laboratory GUI –Main frame has a history tracking panel as well as a working view panel. Analysis node and Dataset node can be created and deleted from the tree. –Input file can also have multiple rows for different sample annotation. User has the option to choose one of the rows as label information for analysis. –Tables of the selected genes for phenotype clustering and their performances can be viewed, and saved. –Has the three types of 2D-projection visualization. –Figures can be viewed, zoomed, and saved as PNG or EPS format. –Support sample/gene annotation view. –Support cluster visualization by hierarchical display –History log can be viewed and saved VISDA-caBIG TM Key Features

Computational Bioinformatics & Bioimaging Laboratory Installation

Computational Bioinformatics & Bioimaging Laboratory VISDA GUI

Computational Bioinformatics & Bioimaging Laboratory VISDA GUI

Computational Bioinformatics & Bioimaging Laboratory VISDA GUI

Computational Bioinformatics & Bioimaging Laboratory VISDA Silver Compatibility VISDA can retrieve data from caArray (can be considered as one caGrid node) by utilizing MAGE-OM APIs. MAGE-OM CDEs (registered in caDSR) used in VISDA are documented. Analysis results got from VISDA are the selected feature set, the "soft-clustering" probabilities of the samples/genes in each cluster and the hierarchical "tree of phenotype" or "tree of gene module" plots which are retained locally. Well documented VISDA APIs. UML documentation of all VISDA components using Enterprise Architect (EA).

Computational Bioinformatics & Bioimaging Laboratory Retrieve Data from caArray

Computational Bioinformatics & Bioimaging Laboratory Retrieve Data from caArray

Computational Bioinformatics & Bioimaging Laboratory VISDA API Document

Computational Bioinformatics & Bioimaging Laboratory VISDA UML Use Case Diagram

Computational Bioinformatics & Bioimaging Laboratory VISDA UML Class Diagram o edu.vt.cbil.visda

Computational Bioinformatics & Bioimaging Laboratory VISDA UML Class Diagram o edu.vt.cbil.visda.data

Computational Bioinformatics & Bioimaging Laboratory VISDA UML Class Diagram o edu.vt.cbil.visda.comp

Computational Bioinformatics & Bioimaging Laboratory VISDA UML Class Diagram o edu.vt.cbil.visda.view