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Table 1 Testing results for simulated data files, requesting 384 and 1536 markers.

From: MarkerSet: a marker selection tool based on markers location and informativity in experimental designs

   Low Density (5K) High Density (40K)
   Score Ratio -r gain Score Ratio -r gain
Basic HI 1002.86    1051.61   
  VI 927.44    1047.9   
  LI 317.92    500   
R HI 1008.3   0.54% 1051.61   0%
  VI 932.38   0.53% 1047.9   0%
  LI 320.59   0.84% 500   0%
MD MD 1879.48    3513.19   
  HI 2774.49 0.99   3959.82 0.96  
  VI 1940.27 0.96   3760.68 0.94  
  LI 428.14 0.80   769.18 0.49  
R + MD MD 2428.19   29.19% 3513.19   0%
  HI 3487.45 0.98 25.70% 3959.82 0.96 0%
  VI 2519.01 0.82 29.83% 3760.68 0.94 0%
  LI 539.56 0.53 26.02% 769.18 0.49 0%
  1. For this purpose, six files with different marker informativity status have been generated with two variables. The first one is the marker density (5K markers – LD for low density or 40K markers – HD for High Density spanned homogeneously on the genome). The second one is marker informativity distribution. Considering a total of 100 reference animals, the following conditions have been explored: markers with heterozygozity values ranging from 50 to 100 (High Informativity, HI), 0 to 100 (Various Informativity, VI) or 0 to 50 (Low Informativity, LI). For each markers panel and condition, the maximal available informativity score (max info), the selected set score, the multidesign/monodesign ratio and the score gain obtained by using the resampling options (-r gain) are detailed. R and MD refer at resampling option activation and multidesign option activation respectively. Scores results are depending on marker density and informativity distribution (better with HI and lower with LI files). Nevertheless, there's only a slight score difference between HI and VI, showing the efficiency of MarkerSet to select the most informative markers. Resampling option is more useful with LD files but can have an impact on the loss of informativity (Ratio) in multidesign mode with LI file.