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ConfeitoGUI: A toolkit for size-sensitive community detection from a correlation network

Author

Listed:
  • Yoshiyuki Ogata
  • Kazuto Mannen
  • Yasuto Kotani
  • Naohiro Kimura
  • Nozomu Sakurai
  • Daisuke Shibata
  • Hideyuki Suzuki

Abstract

Analysis of the large amounts of data accumulated in public databanks can facilitate a more comprehensive understanding of molecular biological processes. Community detection from molecular biological data is paramount in characterizing evolutionary and functional traits of organisms based on gene homology and co-expression, respectively. Although there are common tools to detect local communities from a large network, no toolkit exists for detecting communities that include an element of interest based on size sensitivity, i.e., functionality to obtain local communities with preferred sizes. Herein, we present the ConfeitoGUI toolkit for detecting local communities from a correlation network involving size sensitivity. We compared the toolkit with other common tools for detection in reconstructing communities of microarray experiments of mice. In the results, ConfeitoGUI was observed to be preferable for detecting communities whose sizes are similar to those of original communities compared to other common tools. By changing simple parameters representing sizes for the toolkit, a user can obtain local communities with preferred sizes, which is beneficial for further analysis of members belonging to the communities.

Suggested Citation

  • Yoshiyuki Ogata & Kazuto Mannen & Yasuto Kotani & Naohiro Kimura & Nozomu Sakurai & Daisuke Shibata & Hideyuki Suzuki, 2018. "ConfeitoGUI: A toolkit for size-sensitive community detection from a correlation network," PLOS ONE, Public Library of Science, vol. 13(10), pages 1-18, October.
  • Handle: RePEc:plo:pone00:0206075
    DOI: 10.1371/journal.pone.0206075
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    References listed on IDEAS

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