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Table 3 Correctly identified QTL and false positives using Bayes C

From: QTL fine mapping with Bayes C(π): a simulation study

Size and number of simulated QTL Heritability
Selection of intervals Selection of markers
0.1 0.4 0.7 0.1 0.4 0.7
Large 1 1 1 1 1 1 1
Medium 2 0 2 2 0 1 1
Small 7 4 4 5 3 5 7
False positives 5 3 2 6 3 1
Large 5 1 2 4 1 2 4
Medium 20 1 6 6 2 2 4
Small 75 1 2 2 1 1 2
False positives 7 3 2 7 5 2
Large 50 0 1 1 1 4 5
Medium 200 7 9 8 5 7 5
Small 750 8 16 16 14 16 18
False positives 1 0 0 1 0 1
  1. Number of correctly identified QTL categorised by size of the QTL variance (large, medium or small), and number of false positives, with QTL detection based on the posterior inclusion probability summed up over intervals of 60 adjacent markers or the posterior inclusion probability of individual markers; the 10 best intervals or markers were denoted as QTL; more than one QTL can be present in an interval, so that the total number of QTL identified can be larger than 10.