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A sample of the precision and recall of the variables used is shown in Table 5.
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The impact of averaging multiple UFC samples on the precision of the UFC assessment was evaluated by deriving the intrapatient CV corresponding to the average of two, three and four samples.
Our next step was to determine the importance of C-size anumberber of replicate analyses of the two RIMS-samples for the precision of α- and β-estimates.
We assume these differences were caused by the insufficient sample size of the precision set.
As shown in Figure 2C, without the need of matched control sample, the precision of the single-sample mode of our pipeline was above 50% to identify pSNMs in healthy individuals when the allele fractions were 0.1-0.3 0.1-0.3
Because of our limited sample size, the precision of our estimates is low, but they do indicate findings that warrant further investigation.
As expected, both the number of samples and the precision of estimated P-values increased as a function of increasing h, for both sequential MC and the MCFDR scheme.
Correcting for sample dilution using sample urea improved the precision of measured factors.
We expected that increasing the ΔCq of interest sample and virtual control sample would decrease the precision of double-ratio drqPCR.
The high number of ribosomal reads in the total RNA sample lowers the precision of those measurements.
The effects of these control factors on the number of integral samples and the precision of multilevel fast multipole algorithm (MLFMA) are investigated.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com