A single, sequential, genome-wide test to identity simultaneously all promising areas in a linkage scan

Inflation of type I error occurs when conducting a large number of statisti cal tests in genome-wide linkage scans. Stringent or-levels protect against the high numbers of expected false positives but at the cost of more false negatives. A more balanced tradeoff is provided by the theory of sequentia l analysis, which can be used in a genome scan even when the data are colle cted using a fixed-sample design. Sequential tests allow complete, simultan eous control of both the type I and II errors of each individual test while using the smallest possible sample size for analysis. For fixed samples, t he excess N "saved" can be used in a confirmatory, replication phase of the original findings. Using the theory of sequential multiple decision proced ures [Bechhoffer et al., 1968], we can replace the series of individual mar ker tests with a new single, simultaneous genome-wide test that has multipl e possible outcomes and partitions all markers into two subsets: the "signa l" versus the "noise," with an a priori specifiable genome-wide error rate. These tests are demonstrated for the Haseman-Elston approach, are applied to real data, and are contrasted with traditional fixed-sampling tests in M onte Carlo simulations of repeated genome-wide scans. The method allows eff icient identification of the true signals in a genome scan, uses the smalle st possible sample sizes, saves the excess to confirm those findings, contr ols both types of error, and provides one elegant solution to the debate ov er the best way to balance between false positives and negatives in genome scans. Genet. Epidemiol. 19:301-322, 2000. (C) 2000 Wiley-Liss, Inc.