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thresholdPullDownMenu_Callback sets handles.wThresh and handles.rThresh appropriately based on the selected value, to control the visibility of the walking and running thresholds on the plots.
It also necessary to control the local number of particles per cell (particle rezoning) by increasing or decreasing its value to control the local accuracy.
If ϕ i > 0, then H(ϕ i ) ≈ 1; otherwise, if ϕ i < 0, then H(ϕ i ) ≈ 0, where ϵ is usually a constant with small value to control the speed for H(ϕ i ) to change from 0 to 1.
An alternative and less conservative approach is to adjust the p value to control the FDR.
This ordering is coherent with the hypothesis testing strategy they proposed, based on a new critical value to control the conditional type I error.
The mean pixel intensity for each epitope was determined adjacent to each cell and subtracted from the nuclear value to control for background staining.
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The proposed character segmentation approach is semi-automatic and uses threshold values to control the segmentation process.
Yeast cells treated with AgNPs obtained similar absorbance values to control using the test concentration below 25 mg/L.
Significance testing was based on the F-test using Henderson method III, and 10,000 permutation tests were used to calculate the critical F-value to control the genomewise type I error [34], [35].
Consequently, we used q-values to control for multiple tests.
We calculated adjusted p values to control the false discovery rate (FDR) by the method of Benjamini & Hochberg (shown in the Supplementary Information, Table S1).
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