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Predicting Housekeeping Genes Based on Fourier Analysis

Author

Listed:
  • Bo Dong
  • Peng Zhang
  • Xiaowei Chen
  • Li Liu
  • Yunfei Wang
  • Shunmin He
  • Runsheng Chen

Abstract

Housekeeping genes (HKGs) generally have fundamental functions in basic biochemical processes in organisms, and usually have relatively steady expression levels across various tissues. They play an important role in the normalization of microarray technology. Using Fourier analysis we transformed gene expression time-series from a Hela cell cycle gene expression dataset into Fourier spectra, and designed an effective computational method for discriminating between HKGs and non-HKGs using the support vector machine (SVM) supervised learning algorithm which can extract significant features of the spectra, providing a basis for identifying specific gene expression patterns. Using our method we identified 510 human HKGs, and then validated them by comparison with two independent sets of tissue expression profiles. Results showed that our predicted HKG set is more reliable than three previously identified sets of HKGs.

Suggested Citation

  • Bo Dong & Peng Zhang & Xiaowei Chen & Li Liu & Yunfei Wang & Shunmin He & Runsheng Chen, 2011. "Predicting Housekeeping Genes Based on Fourier Analysis," PLOS ONE, Public Library of Science, vol. 6(6), pages 1-11, June.
  • Handle: RePEc:plo:pone00:0021012
    DOI: 10.1371/journal.pone.0021012
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    References listed on IDEAS

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    1. Hendrik J M de Jonge & Rudolf S N Fehrmann & Eveline S J M de Bont & Robert M W Hofstra & Frans Gerbens & Willem A Kamps & Elisabeth G E de Vries & Ate G J van der Zee & Gerard J te Meerman & Arja ter, 2007. "Evidence Based Selection of Housekeeping Genes," PLOS ONE, Public Library of Science, vol. 2(9), pages 1-5, September.
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