Skip to main content

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