BioGoggles software has been designed for analysis of multivariate data sets such as gene or protein expression data sets. The purpose of BioGoggles is to help discover biomarkers or gene markers. BioGoggles enables visualization of data set with many variables and items and serves as a good starting point for filtering out interesting variables.
The input data set must be in table form were variables are columns and items are rows. Currently BioGoggles support import of comma or tab delimited text files (csv and txt format) either from file or clipboard. The variables must be numeric. Group and name variables can be in text format.
Typically one column will contain the name of the items and another column contains the group or class information such as “cancer” or “normal” or “A”, “B” and “C”. In principle BioGoggles can be used to analyze other sources of multivariate data as long as the input data conforms to this data set format.
￭ Java platform
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BioGoggles provides a method to analyze large data sets using multivariate techniques such as principal component analysis and was developed to allow biologists from a variety of different disciplines to share their methods and findings in the analysis of their datasets. Currently BioGoggles is available for Java 1.5 and above.
Partial list of available applications:
BioGoggles – Java application for the analysis of multivariate data (principal component analysis, linear discriminant analysis, k-nearest neighbors, c4.5 decision tree algorithms)
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Use BioGoggles Crack Free Download to filter out the variables of interest using simple command line options. BioGoggles can be used in 3 steps:
￭ Step 1: Read the data set from standard input.
￭ Step 2: Process the data set for filtering using standard command line options. BioGoggles can perform some filtering by itself.
￭ Step 3: If users want further analysis, then perform the desired operation on the data set (maybe call another tool). Use the data set as input.
This workflow is typical of typical researchers.
1. Launch the tool and write input data in table format.
2. The data set should be formatted as a comma or tab delimited text file with 1 column for names of items and another column for grouping.
This can be done in various ways and the best option would be to tell the user in the GUI how to generate the file.
The following is an example of file format (C:\\Users\\example_data.csv):
3. The user can provide certain filtering options.
4. Check the boxes for analysis and provide the output format.
5. The tool will automatically stop when all the data set has been processed. It will also prompt the user when the current step is complete (pressing ENTER or clicking on check).
6. Run the analysis or GUI step 3 to view the results.
7. The program has a GUI. Users can use it to perform various operations on the filtered data set.
8. The program has three tabs:
1. Analysis: Outputs the data in tabular format with the data set name, name of variable selected and a summary of the values of the filtered variables.
2. Statistics: The details of the items and groups can be examined using several popular statistical packages such as Matlab or R
3. Results: Shows the results of the operation performed on the data set.
Step 1: Read the data set from standard input
Double click the icon named Input data set. A file dialog will open and you can select the data set you wish to load. Click on
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￭ BioGoggles is a free, open source software for multivariate analysis.
￭ Runs on Windows, Linux and Mac operating systems.
￭ Windows executable.exe, and.sh files are available. Source code for the.exe and.sh is also included.
￭ A model is represented as a graph, a tree, or a partition of the space.
￭ Analysis in BioGoggles is done using multidimensional scaling (MDS) and clustering techniques. MDS is a popular method in many fields, including psychometrics, image processing, and pattern recognition.
￭ Only requires a Java version 1.6 or higher
￭ Available from
Procedure to run:
￭ Download and install the latest version of BioGoggles.
￭ Visit the BioGoggles home page:
￭ Click on “To access the most recent version of BioGoggles, click here. Download the latest version.
￭ In windows go to BioGoggles folder and double-click the.exe file.
￭ In linux go to /usr/local/bio-goggles or any other path where BioGoggles is installed.
￭ In Mac, go to Applications folder and open the.app file.
￭ In Mac, additional information is available at
1.0 Initial version of BioGoggles released
2.0 Improvements include new data-mining features (train-test based model) and plugins.
3.0 A new version allows for user defined parameters in MDS analysis, which is included in the documentation and can be found at
4.0 BioGoggles can now be used to analyze and visualize a number of different data types. It is possible to work with even bigger data sets. New visualization tools for Tableau and R have also been added.
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BioGoggles is a java library for the purpose of rapid exploration and application of the analysis of data sets. It is designed to be easy and convenient to understand and install. BioGoggles is a multi-platform tool, supporting the following operating systems: Windows, OS X, and Linux.
Data imported into BioGoggles:
The number of imported items can be limited by the number of available memory. Each row of the table must have a unique name.
Data Dimensions can be automatically or manually set by the user. If the input data dimensions are not pre-defined, BioGoggles will detect the maximum number of rows and columns in the table and set them to the maximum number.
BioGoggles can be used to analyze data sets with three different types of data manipulations:
Select a subset of variables
Transform a subset of variables
Calculate a partial correlation between variables in a subset
Here is the list of variables that can be used:
This is the list of items that can be used to select the variables:
The selection process can be better understood by using a simple example:
Let the data set be:
Since the data set contains 7 variables, 7 items and 15 observations, the input variables are
BioGoggles picks up all variables in the table and assigns them the variable ids. Data are displayed in a 2-dimensional table with the variables on the x-axis and the items on the y-axis.
Since the data set has 2 variables, ids 7 and 8 are chosen. Since, id 7 is not selected, data are displayed in a 3 dimensional table with ids 7, 8 and 9 on the x-axis.
Now, id 8 is selected, so data are displayed in a 2-dimensional table with ids 8, 9 and 10 on the x-axis and id 8 on the y-axis.
By selecting both id 8 and id 9, data set is shown in a 2-dimensional table with ids 8, 9, 10 and 11 on the x-axis and id 8 and id 9 on the y-axis.
The selection process can be further illustrated by a simple example:
Let the data set be:
And the items, variables and their ids are as follows:
Then the output variables and id’s will be as follows:
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A television or monitor with at least a 1920×1080 resolution is required.
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