caa a22 4500 378925989 CHVBK 20180305123617.0 cr unu---uuuuu 161128e20040212xx s 000 0 eng 10.2202/1544-6115.1023 doi (NATIONALLICENCE)gruyter-10.2202/1544-6115.1023 Using Alpha Wisely: Improving Power to Detect Multiple QTL [Elektronische Daten] [Katy L Simonsen, Lauren M McIntyre] The increase in the number of available markers for many experimental populations has led to QTL studies with ever increasing marker numbers and densities. The resulting conundrum is that as marker density increases, so does the multiple testing problem. It is important to re-examine the detection of multiple QTL in light of increasing marker density. We explore through simulation whether existing methods have achieved the maximum possible power for detecting multiple QTL and whether increasing the marker density is an effective strategy for locating multiple QTL. In addition to existing methods, such as the maximum, the CET, and the Benjamini-Hochberg and Benjamini-Yekutieli procedures, we propose and evaluate the complete set of order statistics with their corresponding empirical joint distribution. We examine these statistics in conjunction with a novel application of the alpha-spending approach, providing a less conservative solution to the problem of controlling the false discovery rate (FDR) in multiple tests. We conducted a simulation study to assess the relative power of these approaches as well as their ability to control FDR. We find that several of the new approaches have a reasonable FDR, and can substantially improve the experimenter's ability to detect multiple QTL compared to existing approaches in many cases; however, the Benjamini-Hochberg procedure remains a very reasonable choice. The methods are applied to a nine-trait Oat vernalization dataset. ©2011 Walter de Gruyter GmbH & Co. KG, Berlin/Boston General Biostatistics nationallicence Genetics nationallicence order statistics nationallicence power nationallicence alpha-spending nationallicence FDR nationallicence QTL nationallicence Simonsen Katy L. Purdue University aut McIntyre Lauren M. Purdue University aut Statistical Applications in Genetics and Molecular Biology De Gruyter 3/1(2004-02-12), 1-24 3:1<1 2004 3 sagmb https://doi.org/10.2202/1544-6115.1023 text/html Onlinezugriff via DOI 1 research article jats NATIONALLICENCE 856 40 https://doi.org/10.2202/1544-6115.1023 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Simonsen Katy L. Purdue University aut NATIONALLICENCE 700 1- McIntyre Lauren M. Purdue University aut NATIONALLICENCE 773 0- Statistical Applications in Genetics and Molecular Biology De Gruyter 3/1(2004-02-12), 1-24 3:1<1 2004 3 sagmb CC0 http://creativecommons.org/publicdomain/zero/1.0 nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-gruyter