U.S. Department of Energy

Pacific Northwest National Laboratory

VIBE: Visual Integration for Bayesian Evaluation

The Visual Integration for Bayesian Evaluation (VIBE) software is a visualization tool that allows the user to observe classification accuracies at the class level and evaluate classification accuracies on any subset of available data types based on the posterior probability models defined for the individual and integrated data.

Area of Research: 

This software helps you integrate data from various high-throughput proteomics and metabolomics technologies using a Bayesian approach to integration that uses posterior probabilities to assign class memberships to samples using individual and multiple data sources; these probabilities are based on lower-level likelihood functions derived from standard statistical learning algorithms.

Package icon VIBE Program1.93 MB
Package icon MATLab Runtime167.37 MB
Software Instructions: 

1) Download and install the Matlab Compiler Runtime v7.11, MCRInstaller_v7.11.zip
2) Download VIBE_Program.zip and unzip to a new folder
3) Run VIBEv2_appnote.exe

See file UserManualv2.pdf for information on using the software (this file is included in VIBE_Program.zip).

See file FAQv2.pdf for some frequently asked questions and answers.


Webb-Robertson BJ, McCue LA, Beagley N, McDermott JE, Wunschel DS, Varnum SM, Hu JZ, Isern NG, Buchko GW, Mcateer K, Pounds JG, Skerrett SJ, Liggitt D, Frevert CW. "A Bayesian integration model of high-throughput proteomics and metabolomics data for improved early detection of microbial infections." Pac Symp Biocomput. 2009:451-63.
Abstract on PubMed


All publications that utilize this software should provide appropriate acknowledgement to PNNL and the OMICS.PNL.GOV website. However, if the software is extended or modified, then any subsequent publications should include a more extensive statement, as shown in the Readme file for the given application or on the website that more fully describes the application.



These programs are primarily designed to run on Windows machines. Please use them at your own risk. This material was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor the United States Department of Energy, nor Battelle, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness or any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights.

Portions of this research were supported by the NIH National Center for Research Resources (Grant RR018522), the W.R. Wiley Environmental Molecular Science Laboratory (a national scientific user facility sponsored by the U.S. Department of Energy's Office of Biological and Environmental Research and located at PNNL), and the National Institute of Allergy and Infectious Diseases (NIH/DHHS through interagency agreement Y1-AI-4894-01). PNNL is operated by Battelle Memorial Institute for the U.S. Department of Energy under contract DE-AC05-76RL0 1830.

We would like your feedback about the usefulness of the tools and information provided by the Resource. Your suggestions on how to increase their value to you will be appreciated. Please e-mail any comments to proteomics@pnl.gov

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