To determine positives for calculating PPV, we used final variant calls, which were the product of quality filtering, cross-validation analysis to integrate variant calls from multiple platforms (Methods), and manual review for all mutation types except non-exonic SNVs, for which we included only high confidence variants (Fig. 3a, Supplementary Data 6A D).
The cut-off scores for determining positive expression for each marker were determined by receiver-operating characteristic (ROC) curve analysis as outlined previously (Zlobec et al, 2007).
Thresholds for detection were set to determine positive staining for p53 and TUNEL using BIOQUANT Imaging software (BIOQUANT Image Analysis Corporation, Nashville, TN, USA).
Unstained and isotype control were used to determine positive staining for each marker.
To determine positive factors for cell growth from among the 4 supplements tested, the maximum viable cell concentrations in each culture were evaluated in the normal probability plot.
We examined the clones for RFP induction and for the percentage of positive cells, setting the threshold for determining positive cells from the brightest autofluorescence signal from untransfected NIH-3T3 cells.
Dissection, single cell suspension, and analysis of tumors with minimum contamination by surrounding cells using multi-color flow cytometry allowed determining positive and negative staining for every marker using the fluorescence minus one (FMO) method (Supplementary Figure 1A).
A sample/positive (S/P) ratio of 40%% was the cut-off for determining positive serum samples.
The lab test for determining positive and negative blood types is actually fairly simple.
The receiver operating characteristic (ROC) curve is employed as one of the evaluation criteria, which shows the relationship between the true positive rate (TPR) and the false positive rate (FPR) by varying a threshold for determining positives.
