ConfeitoGUI

★ About ConfeitoGUI

♦ Abstract

ConfeitoGUI is a stand-alone tool for extracting local communities (or network module in this site), based on the Confeito algorithm. The Confeito algorithm is an algorithm to extract network modules from a correlation network.

♦ Usage

• Install of Java Runtime Environment (JRE)
  1. Check the version of JRE: "java -version" on the command prompt in Windows or the terminal in Linux
     (Caution: ConfeitoGUI is performable only on the 64-bit version of JAVA)
  2. 64-bit version of JRE is available at here.
  3. For Windows users, click the “Windows Offline (64-bit)” to install the package.
  4. For Linux users, refer to the site.
• Install of ConfeitoGUI
  • Expand the file "ConfeitoGUI_x.x.x.zip" into a folder.
  • The tool is available here.
• Executionof ConfeitoGUI
  • Doublclick the file "launch.bat" expanded above to execute the tool.
• To know how to analyze using the tool, see the page of example 1.

♦ Steps for analysis Array Data Converter (optional): to change raw data of microarray experiments by Affymetrix and Agilent into a text-formatted file. Correlation Tool: to create a correlation matrix between elements. Cosine and Pearson correlation coefficients are selectable. Preprocessing Tool: to make a two-column list composed of identifiers of elements and names of files including correlation data by elements. Check Tool: to check files of correlation data. FPO (False-Positive-Out) analysis: to select out elements that are highly and excusively correlated to each other and thus, are composed of a network module. Among elements with high correlation coefficients to an element, there can be some elements with high correlation to any (or a lot of) elements; namely “false-positive” elements. ConfeitoGUI can efficiently remove out such false-positive elements from a network module. FNI (False-Negative-In) analysis (optional): for a network module, to select out elements that are specifically related to the module, in spite of low correlation coefficient to the eleements included in the module, namely “false-negative” elements. Using tools for detecting local communities from a network including the FPO analysis, it is difficult to detect such elements, because of low correlation coefficients to elements of the module. By combining the FPO and FNI analyses, ConfeitoGUI can remove out false-positive elements and select out false-negative elements.

♦ Comparison with the other tools for community detection

To check the accuracy of network modules that are extracted from ConfeitoGUI, we obtained a dataset of mouse microarray experiments from Gene Expression Omnibus (GEO), NCBI and compared ConfeitoGUI with the other tools for community detection in their memberships of network modules.

• About GEO
  1. GPL: A platform of gene expression datasets, e.g., microarray and next-generation sequencing.
  2. GSE: Experiments included in GPL.
  3. GSM: Gene expression data belonged to GSE.
  4. In many cases, experiments included in a GSE are similar to each other in their gene expression data.
  5. Namely, experiments (GSMs) in a GSE are expected to belong to the same network module obtained by tools for community detection.
• A dataset, calculation of correlation coefficient, and depiction of correlation network
  1. A dataset of 37,013 chips of Affymetrix mouse microarray (GPL1261) was used (a list of the dataset is available at here).
  2. Cosine correlation coefficients were calculated between experiments to make a correlation matrix.
  3. We depicted correlation networks based on the matrix from 0.50 to 0.99 (0.01 step) as thresholds of the networks.
• The other tool for community detection to be compared
  1. Louvain (Blondel et al., J Stat Mech, 2008): Executable on the Pajek software.
  2. Simulating annealing (Newman and Girvan, Phys Rev E, 2004): Executable on R.
  3. Fast greedy (Clauset et al., Phys Rev E, 2004): Executable on R.

Methods: to check similarity of memberships between network module and GSE experiments F-measure was used for the check. In the field of information retrieval, F-measure, hamonic mean of precision and recall. The precision index here is the proportion of experiments shared with a network module and a GSE () over all experiments in the module (). The recall index here is the proportion of the shared experiments () over all experiments in the GSE (). In the lower figure, the precision index is 6 / 8 = 0.75, and the recall index is 6 / 10 = 0.60. Namely, The value of F-measure is ( 6 + 6 ) / ( 8 + 10 ) = 0.67. The larger F-meausre, the more similar in the memberships of a network module and a GSE. The values of F-measure were calculated for all network modules in the correlation networks with various thresholds. For each correlation network, an average value of F-measure was calculated to compare the values between the tools. Namely, the higher values of average F-measure, the more accurate network modules.

• Results
  1. The lower table represents the average values of F-measure of the tools.
     
     

     Tool	F-measure (average ± SD)
     ConfeitoGUI	0.61 ± 0.34
     Louvain	0.47 ± 0.40
     Simulating annealing	0.40 ± 0.36
     Fast greedy	0.37 ± 0.37

     
     
     
  2. The average value of F-measure of ConfeitoGUI is the highetst and thus, the tool shows the accuracy of network modules.

♦ References

• Ogata Y et al., ConfeitoGUI: a toolkit for community detection from a correlation network in molecular biology, with a function to adjust community size. (submitting)
• Sakurai N et al., KaPPA-View4: a metabolic pathway database for representation and analysis of correlation networks of gene co-expression and metabolite co-accumulation and omics data. Nucleic Acids Res, 39: D677-D684, 2011.
• Ogata Y et al., CoP: a database for characterizing co-expressed gene modules with biological information in plants. Bioinformatics, 26(9): 1267-1268, 2010.
• Ogata Y et al., The prediction of local modular structures in a co-expression network based on gene expression datasets. Genome Inform, 23(1): 117-127, 2009.

♦ The advanced version of ConfeitoGUI

The version in this site is an academic-free version. About the advanced (or full) version of ConfeitoGUI, ask Kazusa DNA Research Institute.

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The KAGIANA Project

(since 2006)

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