title: [Algorithms of likelihood ratio for discriminating full sibling from half sibling].
abstract: OBJECTIVE
  To derive the formulae for likelihood ratio calculation in discriminating full sibling from half sibling with single-parent participation or without parent participation.
  
  
  METHODS
  Null hypothesis and alternative hypothesis were established for discriminating full sibling from half sibling in two circumstances: two children with single-parent and without parent participation. Conditional probabilities of the genetic evidentiary under null and alternative hypotheses were calculated according to the Bayesian theory. The likelihood ratios were established with the conditional probability under alternative hypothesis division that under null hypothesis, followed with simplification. All the formulae were validated in a real case.
  
  
  RESULTS
  While mother or fathers' genetic information available in differentiating full sibling from half sibling, 14 different genotype combinations could be shared by the two detected children at a given locus and the likelihood ratio could be calculated with 5 different formulae respectively. While both parents' genetic information unavailable, 11 different genotype combinations could be shared and the likelihood ratio could be calculated with 7 different formulae respectively. It was validated in a real case that the power of the likelihood ratio method developed for discriminating full sibling from half sibling with single-parent participation was higher than that of the ratio of full sibling index over half sibling index.
  
  
  CONCLUSIONS
  The formulae of likelihood ratio developed are useful for discriminating full sibling from half sibling with single-parent participation or without parent participation.
authors.affiliation: Shanghai Key Laboratory of Forensic Medicine, Institute of Forensic Science, Ministry of Justice, P R China, Shanghai 200063, China. zhaoshuminxl@hotmail.com
authors.forename: Shu-Min
authors.initials: SM
authors.lastname: Zhao
authors.forename: Lin-Na
authors.initials: LN
authors.lastname: Zhang
authors.forename: Su-Hua
authors.initials: SH
authors.lastname: Zhang
authors.forename: Na
authors.initials: N
authors.lastname: Zhang
authors.forename: Zhen-Min
authors.initials: ZM
authors.lastname: Zhao
authors.forename: Cheng-Tao
authors.initials: CT
authors.lastname: Li
mesh_terms: D000465:Algorithms; D000483:Alleles; D001499:Bayes Theorem; D002648:Child; D041321:Chromosomes, Human, X / Q000235:genetics*; D005260:Female; D053803:Forensic Genetics; D005838:Genotype; D006801:Humans; D016013:Likelihood Functions; D008957:Models, Genetic; D010290:Parents; D035781:Siblings; D020080:Tandem Repeat Sequences / Q000235:genetics*