title: Detecting population outliers and null alleles in linkage data: application to GAW12 asthma studies.
abstract: Error-checking procedures are essential to ensure accurate and powerful linkage analysis. Genotype information across families can be used to identify non-amplification of alleles (null alleles) and between-family population sub-structuring, which can result in loss of power in linkage studies if undetected. Methods to identify population outlier individuals and null alleles are applied to genotype data from two asthma genome searches (German and CSGA) available from Genetic Analysis Workshop 12. Two clear population outliers are observed in the German data set, with further evidence of population sub-structuring. In the CSGA data, a significant excess of homozygous individuals is found at D8S1106, suggestive of a null allele at this marker with an estimated frequency of 0.17 (African-American) and 0.20 (Caucasian).
authors.affiliation: Division of Medical and Molecular Genetics, Guy's, King's and St. Thomas' School of Medicine, 8th Floor, Guy's Tower, Guy's Hospital, London SE1 9RT, UK.
authors.forename: S A
authors.initials: SA
authors.lastname: Fisher
authors.forename: C M
authors.initials: CM
authors.lastname: Lewis
authors.forename: L H
authors.initials: LH
authors.lastname: Wise
mesh_terms: D000483:Alleles; D001249:Asthma / Q000453:epidemiology / Q000235:genetics*; D015982:Bias; D002874:Chromosome Mapping / Q000706:statistics & numerical data*; D005784:Gene Amplification; D005787:Gene Frequency / Q000235:genetics; D005819:Genetic Markers; D005828:Genetics, Population; D005838:Genotype; D005858:Germany; D006801:Humans
chemical_list: D005819:Genetic Markers