Reducing sample sizes in genome scans: Group sequential study designs with futility stops

Abstract

Group sequential study designs can greatly facilitate analyses of genetic linkage in complex traits. We recently proposed designs allowing stopping investigations early if the result is significant (König et al. [2001] Am. J. Hum. Genet. 69:590-600), thereby decreasing average sample sizes under the alternative hypothesis. However, average sample sizes were slightly increased under the null hypothesis. We now present designs where the analysis of markers is additionally stopped in case of futility, i.e., if the probability for significant results is sufficiently low. These sequential designs are applied to linkage analyses of single loci. We calculated sample sizes, time points, and critical boundaries for all analyses for 2- and 3-stage designs at an overall significance level of 0.0001. To confirm the validity of asymptotic approximations, Monte Carlo simulations were performed. The utility is demonstrated analyzing genome scan data provided for the Genetic Analysis Workshop 12. Application of the novel sequential designs yields tremendous decreases in average sample sizes, regardless of the size of the underlying genetic effect at investigated loci. Depending on the applied design, almost half of the sample size is spared on average. These enormous savings are expected to have a special impact on costs and time of large-scale studies such as genome scans.

Approximating probabilities of correlated events

“…Therefore, in this case, his algorithm should be applied. On the other hand, as discussed in [3] and sequential analyses of genetic studies [11,12,21], when more than two interim analyses are employed, we have demonstrated that our proposed method is useful. Overall, we think our proposed approach provides a useful alternative for approximating the probability of correlated events.…”

Optimum two-stage designs in case–control association studies using false discovery rate

“…Future improvements in genotyping technology will reduce the cost of genotyping, and the substantial study costs will then depend on only the sample size. To reduce sample size, some investigators (Sobell et al 1993;Kö nig et al 2001Kö nig et al , 2003 have proposed designs that are similar to group sequential methods with application to clinical trials. Although these procedures are considered to be complicated for practical applications, it would be a challenge to improve efficiency by considering the required sample size.…”

Two‐Stage Group Sequential Robust Tests in Family‐Based Association Studies: Controlling Type I Error

“…Applications of group sequential design analysis to genetic studies can be especially useful to reduce cost and time, and therefore to increase efficiency. Konig et al (2001, 2003) utilized the design to calculate sample size and stopping boundaries in linkage studies based on the mean test and association studies on the TDT. Konig & Ziegler (2003) demonstrated the application of group sequential analysis for case‐control studies.…”