Literature DB >> 11793665

Detecting population outliers and null alleles in linkage data: application to GAW12 asthma studies.

S A Fisher1, C M Lewis, L H Wise.   

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).

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Year:  2001        PMID: 11793665     DOI: 10.1002/gepi.2001.21.s1.s18

Source DB:  PubMed          Journal:  Genet Epidemiol        ISSN: 0741-0395            Impact factor:   2.135


  2 in total

1.  Association of polyaminergic loci with anxiety, mood disorders, and attempted suicide.

Authors:  Laura M Fiori; Brigitte Wanner; Valérie Jomphe; Jordie Croteau; Frank Vitaro; Richard E Tremblay; Alexandre Bureau; Gustavo Turecki
Journal:  PLoS One       Date:  2010-11-30       Impact factor: 3.240

2.  A reference haplotype panel for genome-wide imputation of short tandem repeats.

Authors:  Shubham Saini; Ileena Mitra; Nima Mousavi; Stephanie Feupe Fotsing; Melissa Gymrek
Journal:  Nat Commun       Date:  2018-10-23       Impact factor: 14.919

  2 in total

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