Bias in multipoint linkage analysis arising from map misspecification
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Updated: Oct 10, 2026

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
Published on: June 21, 2018
E W Daw1, E A Thompson, E M Wijsman
1Division of Medical Genetics, Department of Medicine, University of Washington, Seattle, Washington 98195-7720, USA. warwick@stat.washington.edu
Abstract:
Multipoint linkage analysis methods are often used in human genetic studies. Although multipoint methods increase power for a linkage analysis and will become essential if use of diallelic markers becomes widespread, the methods in use assume an accurate meiotic marker map. Unfortunately, uncertainties in estimates of between-marker meiotic distances are large. Also, sex-averaged maps are generally used, but recombination rates differ in males and females. Both these types of map misspecification can lead to lod score bias, but such bias has not previously been systematically quantified. We examine multipoint lod score bias arising from these map misspecifications, in both the presence and absence of actual linkage. We define bias as the expected difference between the lod score computed under the misspecified map and that computed under the true map. With actual linkage, any map misspecification causes negative bias in lod scores, resulting in loss of power to detect linkage. In most cases, bias is modest, only reaching clearly detectable levels when both types of misspecification are substantial. In the absence of linkage, map misspecification can cause positive or negative bias: falsely assuming a 1:1 female:male ratio always causes positive bias; using too large a distance gives a positive bias; using too small a distance gives a negative bias. This bias can inflate the false-positive rate, especially when the sample size is modest. We conclude that although current sex-averaged maps are suitable for a first-pass multipoint screen, the potential for bias from map misspecification should be evaluated in following up results from such an analysis.
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