In silico phenotypic screening method of mutants based on statistical modeling of genetically mixed samples

Eli Kaminuma, Naohiko Heida, Takeshi Yoshizumi, Miki Nakazawa, Minami Matsui, Tetsuro Toyoda

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)


In comprehensive functional genomics projects, systematic analysis of phenotypes is vital. However, conventional phenotypic screening is done mainly by imprecise visual observation of qualitative traits, and, therefore, in silico screening techniques for quantitative traits are required. In this report, we propose in silico phenotypic screening method that utilizes a Gaussian mixture model for the trait distribution in the offspring of a mutagenized line and the likelihood ratio test between the estimated Gaussian mixture model and the wild-type single Gaussian model. In order to evaluate the proposed method, we performed a screening experiment using real trait data of Arabidopsis. In this experiment, the proposed screening method properly distinguished the mutant line from the wild-type line. Furthermore, we conducted power analysis of the proposed method and two conventional methods under various simulated conditions of sample size and distribution of trait frequency. The result of the power analysis confirmed the effectiveness of the proposed method compared to the conventional methods.

Original languageEnglish
Pages (from-to)1281-1293
Number of pages13
JournalJournal of Bioinformatics and Computational Biology
Issue number6
Publication statusPublished - Dec 2005
Externally publishedYes


  • 3D
  • Arabidopsis
  • Morphological traits
  • Mutant screening
  • Phenome

Field of Science*

  • 1.6 Biological sciences

Publication Type*

  • 1.1. Scientific article indexed in Web of Science and/or Scopus database


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