On normality, ethnicity, and missing values in quantitative trait locus mapping.
BACKGROUND
This paper deals with the detection of significant linkage for quantitative traits using a variance components approach. Microsatellite markers were obtained for the Genetic Analysis Workshop 14 Collaborative Study on the Genetics of Alcoholism data. Ethnic heterogeneity, highly skewed quantitative measures, and a high rate of missing values are all present in this dataset and well known to impact upon linkage analysis. This makes it a good candidate for investigation.


RESULTS
As expected, we observed a number of changes in LOD scores, especially for chromosomes 1, 7, and 18, along with the three factors studied. A dramatic example of such changes can be found in chromosome 7. Highly significant linkage to one of the quantitative traits became insignificant when a proper normalizing transformation of the trait was used and when analysis was carried out on an ethnically homogeneous subset of the original pedigrees.


CONCLUSIONS
In agreement with existing literature, transforming a trait to ensure normality using a Box-Cox transformation is highly recommended in order to avoid false-positive linkages. Furthermore, pedigrees should be sorted by ethnic groups and analyses should be carried out separately. Finally, one should be aware that the inclusion of covariates with a high rate of missing values reduces considerably the number of subjects included in the model. In such a case, the loss in power may be large. Imputation methods are then recommended.
Labbe
Aurélie
A
Département de Mathématiques et de Statistiques, Université Laval, Québec, G1K7P4, QC, Canada. alabbe@math.uwaterloo.ca
Wormald
Hanna
H
D002874:Chromosome Mapping; D002878:Chromosomes, Human, Pair 1 / Q000235:genetics; D002897:Chromosomes, Human, Pair 7 / Q000235:genetics; D005006:Ethnicity / Q000235:genetics*; D005260:Female; D006801:Humans; D008126:Lod Score; D008297:Male; D008957:Models, Genetic; D010375:Pedigree; D040641:Quantitative Trait Loci / Q000235:genetics*