Power of "Quantitative Trait Loci" detection, single market analisys and of the multiple linear regression

Abstract

In general terms, Quantitative Trait Loci (QTL) mapping differs from other research tools used in genetics since it is, basically, a multiple test procedure. The use of this technique leads to problems related to the genomewise significance level and, consequently, to the power of the test. Using computational data simulation the power of QTL mapping was obtained, carried out through multiple linear regression using stepwise procedures to select markers. Procedures based on single marker analisys, using both the False Discover Rate (FDR) and the Bonferroni criteria to determinate the genomewise significance level were also used. The procedure based on multiple regression, using the stepwise technique, was the most powerful in identifying markers associated to QTL's. However, in cases where its power was less intense, its advantage was the ability to detect only markers strongly associated to QTL's. In comparison to the Bonferroni method, the FDR criterion was in general more powerful, and should be adopted for interval mapping procedures.