title: Pedigree-based relationship inference from complex DNA mixtures.
abstract: We present a general method for analysing DNA mixtures involving relatives that accounts for dropout and drop-in, mutations, silent alleles and population substructure. Whether the aim is to identify the contributors to a mixture who may be related, or to determine the relationship between individuals based on a DNA mixture, both types of problems can be handled by the method and software presented here. We focus on the latter scenario, motivated by non-invasive prenatal paternity testing where the profile of the child is available only in the form of a mixture with the mother's profile. Relationships are represented by pedigrees and can include kinship between more than two individuals. The software is freely available as a graphical user interface in the R package relMix.
authors.affiliation: Zurich Institute of Forensic Medicine, University of Zurich, Zurich, Switzerland. guro.dorum@irm.uzh.ch.
authors.forename: Guro
authors.initials: G
authors.lastname: Dørum
authors.affiliation: Department of Chemistry, Biotechnology and Food Science, Norwegian University of Life Sciences, Aas, Norway.
authors.forename: Navreet
authors.initials: N
authors.lastname: Kaur
authors.affiliation: Zurich Institute of Forensic Medicine, University of Zurich, Zurich, Switzerland.
authors.forename: Mario
authors.initials: M
authors.lastname: Gysi
mesh_terms: D004247:DNA / Q000032:analysis*; D016172:DNA Fingerprinting / Q000379:methods*; D005260:Female; D005787:Gene Frequency; D005838:Genotype; D006801:Humans; D016013:Likelihood Functions; D008297:Male; D008957:Models, Genetic; D010334:Paternity; D010375:Pedigree; D012984:Software
chemical_list: D004247:DNA
keywords: DNA mixtures; Drop-in; Dropout; Kinship; Likelihood ratio; Mutations; NGS; Non-invasive prenatal paternity testing