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Table 2 Number of predictive genes passing the given R 2 threshold in the Geuvadis data and GenoExp data

From: Prediction of gene expression with cis-SNPs using mixed models and regularization methods

threshold Geuvadis data GenoExp data
Lasso ENET LMM BSLMM Lasso ENET LMM BSLMM
0.05 2252 2262 2447 2567 1785 1414 1560 1758
0.10 1144 1145 1145 1266 831 788 734 826
0.20 420 422 383 466 315 309 276 323
0.30 161 162 152 178 156 148 124 160
0.40 75 75 65 76 70 70 56 70
0.50 33 33 25 32 36 32 27 37
0.60 14 14 12 14 25 21 20 24
  1. There are 15,810 and 15,427 genes in the Geuvadis data and GenoExp data, respectively. It can be seen that in both data sets when the given R 2 threshold is large (e.g. ≥0.30) the number of predictive genes passing that value in LMM is less than that of LASSO, ENET or BSLMM, implying that these highly predictive genes may have a sparse genetic architecture