Detecting low-quality markers using map expanders.

Genetic marker data play a crucial role in gene mapping, and genotyping errors may have substantial influence on the power to detect and the precision to locate disease loci. Statistical methods can identify individuals, markers, or pedigrees with a high likelihood of containing genotyping errors, and the putative erroneous genotypes can then be rechecked and either verified, removed, or corrected to reduce the loss of power introduced by errors. We present a method to identify genetic markers with a high genotyping error rate. Genotyping errors are likely to appear as double recombinations which expand the genetic map around the marker. Markers flagged as map expanders (i.e., having an excessive number of double recombinations) can then be reread or regenotyped, or a replacement marker of higher quality can be used instead. The proposed method can be applied to any type of pedigree. Simulation studies of nuclear pedigrees and sib-pairs show that the proposed method generally has high power to identify map expanders when the set of markers is reasonably dense (average intermarker distance of 5 cM), even when the nominal genotyping error rate is low (2%). Not surprisingly, the power to detect map expanders increases with marker heterozygosity and genotyping error rate, and is reduced with increasing intermarker distance. When the method was applied to a real dataset consisting of 56 nuclear pedigrees genotyped for 20 microsatellite markers on chromosome 4, the method diagnosed three markers as map expanders. Subsequent examination of these markers proved that they all had high genotyping error frequencies.