Table 3 Statistical implications for proteins identified as rhythmic in this work

From: Challenges and opportunities for statistical power and biomarker identification arising from rhythmic variation in proteomics

Protein (gene) with 12 hour rhythm

Amplitude (z-score)

Increase in n for maintained power

β (Type II error rate) if uncontrolleda

Zinc-alpha-2-glycoprotein (AZGP1)

0.28

9%

23%

Inter-alpha-trypsin inhibitor heavy chain H2 (ITIH2)

0.3

10%

24%

Fibrinogen alpha chain (FGA)

0.3

10%

24%

Kininogen-1 (KNG1)

0.23

6%

22%

Apolipoprotein A-II (APOA2)

0.27

8%

23%

Immunoglobulin kappa light chain (IGK)

0.27

8%

23%

Plasminogen (PLG)

0.22

5%

22%

Immunoglobulin heavy constant mu (IGHM)

0.31

11%

24%

Immunoglobulin kappa constant (IGKC)

0.27

8%

23%

Protein (gene) with 24 hour rhythm

Amplitude (z-score)

Increase in n for maintained power

β (Type II error rate) if uncontrolled

Plasminogen (PLG)

0.37

16%

26%

Apolipoprotein C-III (APOC3)

0.41

20%

28%

Fibrinogen alpha chain (FGA)

0.32

11%

24%

Fibrinogen beta chain (FGB)

0.31

11%

24%

Complement factor H (CFH)

0.29

9%

24%

Apolipoprotein E (APOE)

0.37

16%

26%

  1. aFor baseline calculations a β of 20% was used, or a statistical power of 80%.