Amir R Kermany1, Laure Segurel1, Tiffany R Oliver2, Molly Przeworski1. 1. Department of Human Genetics and Howard Hughes Medical Institute, University of Chicago, Chicago, IL 60637, USA and Department of Biology, Spelman College, Atlanta, GA 30314, USADepartment of Human Genetics and Howard Hughes Medical Institute, University of Chicago, Chicago, IL 60637, USA and Department of Biology, Spelman College, Atlanta, GA 30314, USA. 2. Department of Human Genetics and Howard Hughes Medical Institute, University of Chicago, Chicago, IL 60637, USA and Department of Biology, Spelman College, Atlanta, GA 30314, USA.
Abstract
MOTIVATION: An estimated 10-30% of clinically recognized conceptions are aneuploid, leading to spontaneous miscarriages, in vitro fertilization failures and, when viable, severe developmental disabilities. With the ongoing reduction in the cost of genotyping and DNA sequencing, the use of high-density single nucleotide polymorphism (SNP) markers for clinical diagnosis of aneuploidy and biomedical research into its causes is becoming common practice. A reliable, flexible and computationally feasible method for inferring the sources of aneuploidy is thus crucial. RESULTS: We propose a new method, TroX, for analyzing human trisomy data using high density SNP markers from a trisomic individual or product of conception and one parent. Using a hidden Markov model, we infer the stage of the meiotic error (I or II) and the individual in which non-disjunction event occurred, as well as the crossover locations on the trisomic chromosome. A novel and important feature of the method is its reliance on data from the proband and only one parent, reducing the experimental cost by a third and enabling a larger set of data to be used. We evaluate our method by applying it to simulated trio data as well as to genotype data for 282 trios that include a child trisomic for chromosome 21. The analyses show the method to be highly reliable even when data from only one parent are available. With the increasing availability of DNA samples from mother and fetus, application of approaches such as ours should yield unprecedented insights into the genetic risk factors for aneuploidy. AVAILABILITY AND IMPLEMENTATION: An R package implementing TroX is available for download at http://przeworski.uchicago.edu/.
MOTIVATION: An estimated 10-30% of clinically recognized conceptions are aneuploid, leading to spontaneous miscarriages, in vitro fertilization failures and, when viable, severe developmental disabilities. With the ongoing reduction in the cost of genotyping and DNA sequencing, the use of high-density single nucleotide polymorphism (SNP) markers for clinical diagnosis of aneuploidy and biomedical research into its causes is becoming common practice. A reliable, flexible and computationally feasible method for inferring the sources of aneuploidy is thus crucial. RESULTS: We propose a new method, TroX, for analyzing human trisomy data using high density SNP markers from a trisomic individual or product of conception and one parent. Using a hidden Markov model, we infer the stage of the meiotic error (I or II) and the individual in which non-disjunction event occurred, as well as the crossover locations on the trisomic chromosome. A novel and important feature of the method is its reliance on data from the proband and only one parent, reducing the experimental cost by a third and enabling a larger set of data to be used. We evaluate our method by applying it to simulated trio data as well as to genotype data for 282 trios that include a child trisomic for chromosome 21. The analyses show the method to be highly reliable even when data from only one parent are available. With the increasing availability of DNA samples from mother and fetus, application of approaches such as ours should yield unprecedented insights into the genetic risk factors for aneuploidy. AVAILABILITY AND IMPLEMENTATION: An R package implementing TroX is available for download at http://przeworski.uchicago.edu/.
Authors: S L Sherman; N Takaesu; S B Freeman; M Grantham; C Phillips; R D Blackston; P A Jacobs; A E Cockwell; V Freeman; I Uchida Journal: Am J Hum Genet Date: 1991-09 Impact factor: 11.025
Authors: Augustine Kong; John Barnard; Daniel F Gudbjartsson; Gudmar Thorleifsson; Gudrun Jonsdottir; Sigrun Sigurdardottir; Bjorgvin Richardsson; Jonina Jonsdottir; Thorgeir Thorgeirsson; Michael L Frigge; Neil E Lamb; Stephanie Sherman; Jeffrey R Gulcher; Kari Stefansson Journal: Nat Genet Date: 2004-10-03 Impact factor: 38.330