Table 2 Genic and regulatory features significantly contribute to predicting transcriptional consequences of CNVs.

From: Functional annotation of rare structural variation in the human brain

 

CMC

CMC_HBCC

CNV class

Variable

Beta

SE

T

P

Beta

SE

T

P

Beta

SE

T

P

Deletions

Exonic Proportion

−1.7762

0.0664

−26.77

9.9E−158

−2.0563

0.0852

−24.12

1.8E−128

−1.5571

0.0939

−16.59

8.68E−62

Enhancer sum

−0.0152

0.0083

−1.83

6.7E−02

−0.0093

0.0094

−0.99

3.2E−01

−0.0188

0.0112

−1.69

9.14E−02

Promoter proportion

−0.1726

0.0589

−2.93

3.4E−03

−0.1719

0.0747

−2.30

2.1E−02

−0.0872

0.0843

−1.04

3.01E−01

SV Length

−2.14E−07

1.46E-08

−14.70

6.9E−49

−1.92E−07

1.70E−08

−11.26

2.0E−29

−1.89E−07

3.42E−08

−5.53

3.19E−08

Within TAD

−0.0090

0.0022

−4.03

5.7E−05

−0.0113

0.0031

−3.61

3.0E−04

−0.0046

0.0028

−1.65

9.83E−02

Duplications

Exonic Proportion

0.7825

0.0352

22.22

3.0E−109

1.1285

0.0546

20.67

1.0E−94

0.5043

0.0442

11.42

3.43E−30

Enhancer sum

−0.0157

0.0027

−5.77

8.1E−09

0.0015

0.0062

0.24

8.1E−01

−0.0164

0.0030

−5.42

5.84E−08

Promoter proportion

0.3735

0.0326

11.45

2.5E−30

0.3523

0.0509

6.92

4.5E−12

0.3438

0.0403

8.54

1.37E−17

SV Length

3.99E-07

2.60E-08

15.34

4.6E−53

4.07E−07

3.52E−08

11.58

5.3E−31

3.05E−07

3.68E−08

8.30

1.04E−16

Within TAD

0.0046

0.0036

1.26

2.1E−01

0.0072

0.0052

1.38

1.7E−01

0.0038

0.0045

0.86

3.89E−01

  1. Coefficients of linear regression model to predict expression z-scores in deletions and duplications, across all samples and stratified by cohort.