A permutation solution to the problem of genetic differentiation is presented. The focus is on determining whether there are any differences between two populations. The ability to obtain plausible genetic heterogeneities by combining the information of several loci differs depending on the method used, so no statistical test uniformly dominates the others. The procedure proposed here is robust and flexible with regard to the possible configurations of the global alternative hypothesis. Moreover, such a procedure guarantees the rejection of the global hypothesis with probability alpha when all null (local) hypotheses are true. (c) 2004 Elsevier B.V. All rights reserved.
Salmaso, L., Solari, A. (2006). Nonparametric iterated combined tests for genetic differentiation. COMPUTATIONAL STATISTICS & DATA ANALYSIS, 50(4), 1105-1112 [10.1016/j.csda.2004.11.005].
Nonparametric iterated combined tests for genetic differentiation
SOLARI, ALDO
2006
Abstract
A permutation solution to the problem of genetic differentiation is presented. The focus is on determining whether there are any differences between two populations. The ability to obtain plausible genetic heterogeneities by combining the information of several loci differs depending on the method used, so no statistical test uniformly dominates the others. The procedure proposed here is robust and flexible with regard to the possible configurations of the global alternative hypothesis. Moreover, such a procedure guarantees the rejection of the global hypothesis with probability alpha when all null (local) hypotheses are true. (c) 2004 Elsevier B.V. All rights reserved.
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
