Belknap J K, Mitchell S R, O'Toole L A, Helms M L, Crabbe J C
Research Service, VA Medical Center, Oregon Health Sciences University, Portland 97201, USA.
Behav Genet. 1996 Mar;26(2):149-60. doi: 10.1007/BF02359892.
Effective mapping strategies for quantitative trains must allow for the detection of the more important quantitative trait loci (QTLs) while minimizing false positives. Type I (false-positive) and Type II (false-negative) error rates were estimated from a computer simulation of QTL mapping in the BXD recombinant inbred (RI) set compromising 26 strains of mice, and comparisons made with theoretical predictions. The results are generally applicable to other RI sets when corrections are made for differing strain numbers and marker densities. Regardless of the number or magnitude of simulated QTLs contributing to the trait variance, the p value necessary to provide adequate protection against both Type I (alpha=.0001) and Type II (beta=.2) errors, a QTL would have to account for more than half of the between-strain (genetic) variance if the BXD or similar set was used alone. In contrast, a two-step mapping strategy was also considered, where RI strains are used as a preliminary screen for QTLs to be specifically tested (confirmed) in an F2 (or other) population. In this case, QTLs accounting for approximately 16% of the between-strain variance could be detected with an 80% probability in the BXD set when alpha = 0.2. To balance the competing goals of minimizing Type I and II errors, an economical strategy is to adopt a more stringent alpha initially for the RI screen, since this requires only a limited genome search in the F2 of the RI-implicated regions (approximately 10% of the F2 genome when p < .01 in the RIs). If confirmed QTLs do not account in the aggregate for a sufficient proportion of the genetic variance, then a more relaxed alpha value can be used in the RI screen to increase the statistical power. This flexibility in setting RI alpha values is appropriate only when adequate protection against Type I errors comes from the F2 (or other) confirmation test(s).
针对数量性状的有效定位策略必须能够检测到更重要的数量性状基因座（QTL），同时尽量减少假阳性。通过对由26个小鼠品系组成的BXD重组近交系（RI）群体进行QTL定位的计算机模拟，估计了I型（假阳性）和II型（假阴性）错误率，并与理论预测进行了比较。当对不同的品系数和标记密度进行校正时，这些结果通常适用于其他RI群体。无论对性状变异有贡献的模拟QTL的数量或大小如何，如果单独使用BXD或类似群体，为了同时提供足够的保护以防止I型（α = 0.0001）和II型（β = 0.2）错误，一个QTL必须解释超过一半的品系间（遗传）变异。相比之下，还考虑了一种两步定位策略，即先将RI品系用作QTL的初步筛选，然后在F2（或其他）群体中对特定的QTL进行专门测试（确认）。在这种情况下，当α = 0.2时，在BXD群体中，能够以80%的概率检测到解释约16%品系间变异的QTL。为了平衡最小化I型和II型错误这两个相互竞争的目标，一种经济的策略是在RI筛选时最初采用更严格的α值，因为这只需要在RI相关区域的F2中进行有限的基因组搜索（当RI中的p < 0.01时，约为F2基因组的10%）。如果确认的QTL总体上没有解释足够比例的遗传变异，那么可以在RI筛选中使用更宽松的α值以提高统计效力。只有当来自F2（或其他）确认测试能够提供足够的保护以防止I型错误时，设置RI α值的这种灵活性才是合适的。
