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Table 2 Linear regression modeling of variation versus input biomass and mean relative abundance. Summary of the linear regression model (a) and predicted variation values for a subset of 16S rRNA gene copies/microliter and mean relative abundance values (b)

From: Quantification of variation and the impact of biomass in targeted 16S rRNA gene sequencing studies

a. Model

Estimate

Standard error

t value

p value

  

(Intercept)

1.43238

0.12556

11.408

< 2.2E−16

  

log10 copies/microliter

− 0.2816

0.04905

− 5.741

6.93E−8

  

log10 mean relative abundance

− 0.54936

0.06927

− 7.931

1.13E−12

  

Residual standard error

0.5196

     

Multiple R-squared

0.4496

     

Adjusted R-squared

0.4407

     

F statistic

50.25 on DF (2123)

    

b. Prediction

 

Mean relative abundance (%)

 

Copies/microliter

1

5

10

25

50

Low biomass

10

0.5723

1.7313

2.7888

5.2376

8.4370

Medium biomass

1000

0.2865

0.8668

1.3963

2.6224

4.2242

High biomass

100,000

0.1435

0.4340

0.6991

1.3130

2.1150