Table 3

Principal component regression analysis: principal components PC1 to PC4

PC1

PC2

PC3

PC4





YTN1

YTN2

YTN1

YTN2

YTN1

YTN2

YTN1

YTN2


Percent variance explained by each PC

27

29

20

19

15

15

12

10

Effect of PCs on response variables

dN

0.118

-0.026

-0.172

0.166*

0.015

0.199

-0.065

0.144

dS

-0.001

-0.009

-0.122*

-0.046

-0.161

-0.094

0.073

0.096

dS'

-0.014

-0.019

-0.053

-0.030

-0.108

-0.114

0.082

0.078

dN/dS

0.114

-0.028

-0.113*

0.194

0.106

0.240

-0.123*

0.117

dN/dS'

0.132

-0.025

-0.169

0.190

0.064

0.248

-0.106

0.122

Residuals dN-dS

0.124

-0.024

-0.141

0.189

0.071

0.239

-0.093

0.120

Contribution of predictor variables to each PC

CAI

-0.095

0.228

0.535

-0.356

0.419

0.435

0.069

0.405

Expression level

0.008

0.289

0.515

-0.297

0.154

0.468

-0.596

-0.280

Expression variability

0.290

-0.105

-0.350

0.616

0.454

-0.050

0.132

-0.009

kin

0.538

0.423

0.195

0.413

0.288

0.333

0.061

0.140

kout

0.464

0.453

-0.047

0.052

-0.419

-0.353

-0.023

-0.157

Centrality

0.623

0.564

0.176

0.312

-0.095

-0.010

0.067

0.050

Essentiality

-0.115

0.230

0.415

-0.241

-0.102

-0.506

0.776

0.634

GO

0.011

0.314

0.287

-0.277

-0.562

-0.313

-0.109

-0.556


No single variable dominates the rate of protein evolution. *P < 0.05, P < 0.01, P < 0.001. PC, principal component.

Jovelin and Phillips Genome Biology 2009 10:R35   doi:10.1186/gb-2009-10-4-r35

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