The essence of linkage-based imprinting detection: comparing power, type 1 error, and the effects of confounders in two different analysis approaches.

Imprinting is critical to understanding disease expression. It can be detected using linkage information, but the effects of potential confounders (heterogeneity, sex-specific penetrance, and sex-biased ascertainment) have not been explored. We examine power and confounders in two imprinting detection approaches, and we explore imprinting-linkage interaction. One method (PP) models imprinting by maximising lod scores w.r.t. parent-specific penetrances. The second (DRF) approximates imprinting by maximising lods over differential male-female recombination fractions. We compared power, type 1 error, and confounder effects in these two methods, using computer-simulated data. We varied heterogeneity, penetrance, family and dataset size, and confounders that might mimic imprinting. Without heterogeneity, PP had more imprinting-detecting power than DRF. PP's power increased when parental affectedness status was ignored, but decreased with heterogeneity. With heterogeneity, type 1 error increased dramatically for both methods. However, DRF's power also increased under heterogeneity, more than was attributable to inflated type 1 error. Sex-specific penetrance could increase false positives for PP but not for DRF. False positives did not increase on ascertainment through an affected "mother". For PP, non-penetrant individuals increased information, arguing against using affected-only methods. The high type 1 error levels under some circumstances means these methods must be used cautiously.