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To introduce the method of avuncular index (AI) calculation.Identity by decent coefficient, coancestry coefficient and AI law were employed in identification of uncle-niece relationship, when autosomal STR loci were detected to determine controversial uncle-niece relationship.The results of AI calculation were coincidental using identity by descent coefficien, coancestry coefficient and AI law.The results are coincidental using three methods in the different situations. AI index is higher with participation of children's mother.

To introduce a new method for calculating the paternity index (PI).Assuming that each allele from parents has undergone a transition before it segregates and transmits to child. The transition probability is 1 when parent allele is the same as child's, the transition probability is 0 when parent allele is different from the child's. Every allele has a transmission probability with 0.5. Base on these theories, it is easy to gain the probability that child inherits an allele from the alleged father or mother. Thus, the X value (numerator) and Y value (denominator) of PI formula can be calculated, as unknown man provide an allele for child with the allele frequency.A general formula that calculated the PI for trios, duos and missing child cases was deduced.The new method is practical in all kinds of forensic paternity case.

To introduce a method of calculating the paternity index (PI) for autosomal codominant markers when the mutation is encountered.Assuming mutation arises with a mutational probability before an allele segregates and transmits to child with 1/2 chance, the probability of a random man giving an allele to child is the allele frequency in population. Considering only one mutation event in one case, the mutant allele can be determined by comparing the allele between parents and child. Furthermore, the probability of child's genotype can be calculated to identify the father between a tested man and a random male. Subsequently, the PI can be calculated.Formula of PI was deduced for trios, duos and missing child cases, including maternal mutation.The method is easy to understand and useful in paternity testing.

To investigate the application of ITO method and discriminant functions method in full sibling and half sibling identification.Five hundred pairs of full siblings (FS), 50 pairs of half siblings (HS) and 500 pairs of unrelated individuals (UR) were genotyped by PowerPlex 16 system. Full sibling index (FSI), half sibling index (HSI) and the FSI:HSI ratio were calculated with ITO method. Allelic matching of each pair of the three groups was compared. The locus numbers of no-allele sharing (x0), half-allele sharing (x1) and two-alleles sharing (x2) were calculated, respectively. The discriminant functions about full-siblings, half-siblings and unrelated individuals (UR) were established by SPSS 13.0 statistical software.(1) Regard FSIor = 19 or FSI1 as the standard of distinguishing full sibling from unrelated individual, the alternate correct percentage was 96.4%. Regard HSIor = 19 or HSI1 as the standard of distinguishing half sibling from unrelated individual, the alternate correct percentage was 85.3%. Regard FSI:HSIor = 1 or FSI:HSI1 as the standard of distinguishing full sibling from half sibling, the alternate correct percentage was 87.5%. (2) Four groups of discriminant functions were established. The alternate correct percentage of these discriminant functions were 84.4%-97.7%, with the highest one in full sibship-unrelated individual group.Both ITO method and discriminant functions method are efficient in identification of full sibling or half sibling.