Summary: VISDA (Visual Statistical Data Analyzer) is a caBIG™ analytical tool for cluster modeling, visualization and discovery that has met silver-level compatibility under the caBIG initiative. Being statistically principled and visually interfaced, VISDA exploits both hierarchical statistics modeling and human gift for pattern recognition to allow a progressive yet interactive discovery of hidden clusters within high dimensional and complex biomedical datasets. The distinctive features of VISDA are particularly useful for users across the cancer research and broader research communities to analyze complex biological data.
Bibliographical noteFunding Information:
The authors would like to thank members of the caBIGTM Integrative Cancer Research WorkSpace for reviewing VISDA documentation and/or providing helpful feedback on VISDA development. Thanks also go to the caArray Team at the National Cancer Institute for providing caArray testing datasets. This work is supported by the National Cancer Institute of the NIH under Grants caBIGTM-VISDA; CA109872; CA100970; CA096483.