[Full sibling identification based on the number of matched STR locus]

Fa Yi Xue Za Zhi. 2009 Oct;25(5):341-4.
[Article in Chinese]

Abstract

Objective: To establish and evaluate the method of matched locus numbers in full sibling identification.

Methods: Two hundred and eighty full sibling (FS) pairs and 2003 unrelated individual (UI) pairs were genotyped with Identifiler system. The number of locus matched with 0 identical allele (A0), matched with 1 allele (A1) or matched with 2 alleles (A2) were counted and full sibling index (FSI) were calculated based on ITO method. Fisher discriminant functions were established based on the numbers of matched STR locus or FSI. Power of different Fisher discriminant functions was statistically analyzed.

Results: The distribution of A1 and A2 in FS group and that of A0 and A1 in UI group were in accord with normal distribution. Contrarily, A0 in FS group and A2 in UI group fitted to skew distribution, respectively. Difference of A1 distribution was not statistically significant in the two groups (P>0.01). The established Fisher discriminant functions based on A0 and A2 for each group were Z(FS)=0.99817A0+4.24442A2-12.77970 and Z(UI)=2.01456A0+1.54658A2-7.28076, respectively, the average error probability of which was as low as 0.0490. The power of discrimination for full sibling showed no statistically significant difference between ITO method and the established Fisher discriminant functions.

Conclusion: The number of matched STR locus in Identifiler system is a valuable method in full sibling identification. The discriminating power of the established Fisher discriminant functions based on the matched STR locus number is similar with that of classic ITO method in full sibling identification.

Publication types

  • English Abstract
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Alleles
  • Discriminant Analysis
  • Forensic Genetics / methods
  • Genetics, Population*
  • Humans
  • Likelihood Functions
  • Polymerase Chain Reaction / methods
  • ROC Curve
  • Siblings*
  • Tandem Repeat Sequences / genetics*