TY - JOUR
T1 - Sex specificity, life-span QTLs, and statistical power
AU - Curtsinger, James W.
PY - 2002/12/1
Y1 - 2002/12/1
N2 - Most of the quantitative trait loci (QTLs) that have been found to influence life span in Drosophila and Mus organisms are reported to have genetic effects limited to one sex. Here I study the statistical properties of sex-limited QTLs by randomly sampling data from an exceptionally large Drosophila experiment, and then asking how sample size influences outcomes. The sampling study suggests that, for the particular data analyzed here, even moderately large experiments, of the order of 104 individuals, can have a high probability of detecting sex-limited effects when they are not actually present. If a particular QTL is present in both sexes, and if the probability of detecting it in each sex is moderately high, say 80%, then there is a 32% chance of erroneously concluding that there is sex specificity. A comparison of interval mapping and composite interval mapping methods of data analysis suggests that the latter can inflate the appearance of sex specificity and sexual antagonism, depending on the choice of number of background covariates in the analysis. Conclusive evidence for sex-limited QTLs will require demonstration that results are robust to methods of statistical analysis, and experimental replication.
AB - Most of the quantitative trait loci (QTLs) that have been found to influence life span in Drosophila and Mus organisms are reported to have genetic effects limited to one sex. Here I study the statistical properties of sex-limited QTLs by randomly sampling data from an exceptionally large Drosophila experiment, and then asking how sample size influences outcomes. The sampling study suggests that, for the particular data analyzed here, even moderately large experiments, of the order of 104 individuals, can have a high probability of detecting sex-limited effects when they are not actually present. If a particular QTL is present in both sexes, and if the probability of detecting it in each sex is moderately high, say 80%, then there is a 32% chance of erroneously concluding that there is sex specificity. A comparison of interval mapping and composite interval mapping methods of data analysis suggests that the latter can inflate the appearance of sex specificity and sexual antagonism, depending on the choice of number of background covariates in the analysis. Conclusive evidence for sex-limited QTLs will require demonstration that results are robust to methods of statistical analysis, and experimental replication.
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U2 - 10.1093/gerona/57.12.B409
DO - 10.1093/gerona/57.12.B409
M3 - Article
C2 - 12456730
AN - SCOPUS:0036902923
SN - 1079-5006
VL - 57
SP - B409-B414
JO - Journals of Gerontology - Series A Biological Sciences and Medical Sciences
JF - Journals of Gerontology - Series A Biological Sciences and Medical Sciences
IS - 12
ER -