Statistical estimation of diagnosis with genetic markers based on decision tree analysis of complex disease

  • Authors:
  • Liu Hui;Gai Liping

  • Affiliations:
  • College of Medical Laboratory, Dalian Medical University, Dalian 116027, China;College of Medical Laboratory, Dalian Medical University, Dalian 116027, China

  • Venue:
  • Computers in Biology and Medicine
  • Year:
  • 2009

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Abstract

To explore combinations of genetic markers and to estimate their joint action, decision trees are built on the basis of marker frequencies in both disease and control groups. Youden's index (0.1-0.9 for a single marker) is calculated for genetic markers with different diagnostic capacities. When 23 single genetic markers with diagnostic power 0.10 are combined, the resulting diagnostic power is 0.5. Medium diagnostic power (Youden's index 0.7) can be obtained by combining four low effect diagnostic items. High diagnostic power (Youden's index 0.9) can be obtained by combining either eight low power items or four medium power ones. This implies that selection of about 100 genetic markers, differing in capacity to distinguish between the disease and control groups by (say) 10%, will meet the requirement for clinic diagnosis. Thus, diagnosis of complex diseases by genetic markers is possible through the discovery and characterization of markers throughout the human genome and the development of genotyping technology.