Skip to main content

Table 1 CIC data: Method comparison for estimating the Δ Δ C q -value

From: Unaccounted uncertainty from qPCR efficiency estimates entails uncontrolled false positive rates

 

Estimate

se

t-value

df

p-value

LCL

UCL

MGST1 vs GAPDH

       

EC

–8.62

1.62

–5.31

21

2.92·10−5

–12

–5.24

EC&VA1

–8.62

1.66

–5.18

21

3.89·10−5

–12.1

–5.16

EC&VA2

–8.62

1.67

–5.17

21

4.04·10−5

–12.1

–5.15

Bootstrap

–8.66

2.06

  

1.00·10−3

–12.5

–4.41

MGST1 vs ACTB

       

EC

–8.98

1.61

–5.57

21

1.57·10−5

–12.3

–5.63

EC&VA1

–8.98

1.65

–5.45

21

2.08·10−5

–12.4

–5.56

EC&VA2

–8.98

1.65

–5.45

21

2.10·10−5

–12.4

–5.55

Bootstrap

–8.98

2.09

  

1.00·10−3

–12.7

–4.48

MMSET vs GAPDH

       

EC

0.679

0.585

1.16

21

2.59·10−1

–0.538

1.9

EC&VA1

0.679

0.587

1.16

21

2.60·10−1

–0.541

1.9

EC&VA2

0.679

0.589

1.15

21

2.62·10−1

–0.545

1.9

Bootstrap

0.688

0.678

  

3.12·10−1

–0.656

2

MMSET vs ACTB

       

EC

0.318

0.962

0.331

21

7.44·10−1

–1.68

2.32

EC&VA1

0.318

0.962

0.331

21

7.44·10−1

–1.68

2.32

EC&VA2

0.318

0.964

0.33

21

7.45·10−1

–1.69

2.32

Bootstrap

0.342

0.987

  

7.05·10−1

–1.68

2.13

  1. EC efficiency corrected LMM estimate ignoring the uncertainty of the efficiency estimates. EC&VA1 EC and variance adjusted LMM estimate using the delta method. EC&VA2 EC and variance adjusted LMM estimate using Monte Carlo integration. Bootstrap estimate by the bootstrap described in Section “Inference for Δ Δ C q by the bootstrap method” fitting the LMM and using the EC estimate. Bootstrap shows the mean and standard deviation of 2000 bootstrap samples using the EC estimate. The last two columns show the 95 % lower and upper confidence interval limits