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Table 2 Summary of results for the simulated data with main and epistatic effects

From: Fast empirical Bayesian LASSO for multiple quantitative trait locus mapping

Algorithm Parameters PE ± STE* Number of effects†‡ CPU time (mins)
  (0.001, 0.001) 16.49 ± 0.8908 25/0 13.5 3.4
  (0.01, 0.01) 15.95 ± 0.7477 28/0 12.46 3.4
  (0.05, 0.05) 15.89 ± 0.7498 30/0 11.72 3.4
  (0.1, 0.1) 15.81 ± 0.8359 30/0 11.72 3.4
EBLASSO (0.5, 0.5) 15.86 ± 0.7717 31/0 11.57 3.4
  (1, 1) 16.07 ± 0.7203 29/0 12.31 3.4
  (0.5, 0.1) 16.14 ± 0.8557 28/0 12.5 3.4
  (-0.01, 0.1) 15.92 ± 1.0161 32/1 11.31 3.4
  (-1, 0.0001) - 14/1 21.22 2,760.0
EB (-1, 0.0005) - 13/1 12.15 4,140.0
  (-1, 0.001) - 22/1 0.25 14,940.0
  (-1, 0.01) - 8/0 0.01 2,760.0
  1. Parameters are (a, b) for the EBLASSO, and (τ, ω) for the EB.
  2. *The average PE and the standard error were obtained from ten-fold cross validation.
  3. The number of effects and residual variance were obtained using all 1000 samples not from cross validation.
  4. The first number is the number of true positive effects; the second number is number of false positive effects. All the effects counted have a p-value ≤ 0.05.