Using X-chromosomal markers in relationship testing: Calculation of likelihood ratios taking both linkage and linkage disequilibrium into account
Artikel i vetenskaplig tidskrift, 2011

X-chromosomal markers in forensic genetics have become more widely used during recent years, particularly for relationship testing. Linkage and linkage disequilibrium (LD) must typically be accounted for when using close X-chromosomal markers. Thus, when producing the weight-of-evidence, given by a DNA-analysis with markers that are linked, the normally used product rule is invalid. Here we present an implementation of an efficient model for calculating likelihood ratios (LRs) with markers on the X-chromosome which are linked and in LD. Furthermore, the model was applied on several cases based on data from the eight X-chromosomal loci included in the Mentype® Argus X-8 (Biotype). Using a simulation approach we showed that the use of X-chromosome data can offer valuable information for choosing between the alternatives in each of the cases we studied, and that the LR can be high in several cases. We demonstrated that when linkage and LD were disregarded, as opposed to taken into account, the difference in calculated LRs could be considerable. When these differences were large, the estimated haplotype frequencies often had a strong impact and we present a method to estimate haplotype frequencies. Our conclusion is that linkage and LD should be accounted for when using the tested set of markers, and the used model is an efficient way of doing so.

Författare

Andreas O Tillmar

Linköpings universitet

T Egeland

Universitetet i Oslo

OsloMet – storbyuniversitetet

Bertil Lindblom

Linköpings universitet

G Holmlund

Linköpings universitet

Petter Mostad

Chalmers, Matematiska vetenskaper, Matematisk statistik

Göteborgs universitet

Forensic Science International: Genetics

1872-4973 (ISSN) 18780326 (eISSN)

Vol. 5 5 506-511

Styrkeområden

Livsvetenskaper och teknik (2010-2018)

Ämneskategorier

Bioinformatik och systembiologi

Sannolikhetsteori och statistik

DOI

10.1016/j.fsigen.2010.11.004

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Senast uppdaterat

2018-05-08