Figure 5 shows smoothing results obtained using two different threshold values.
By using two different threshold values (log2 ratio >|0.5|, and |1|), we distinguished low-level CNAs, which can result from aneuploidy, from high-level CNAs, which result from focal amplification or deletions of chromosome regions.
To determine the threshold that should be set for identifying true mutations, the data were first analyzed using three different thresholds to optimize the sensitivity of the assay.
After correcting for the false mutation proportion, we explored mutation calling using three different thresholds for optimization (Additional file 1: Table S1).
We analyzed canonical pathways using three different thresholds of gene expression (1.5-fold up/downregulation, 2.0-fold up/downregulation, and 3.0-fold up/downregulation; Supplementary files 3 5).
Seven studies reported the number and/or percentage of dextrose injections when BGL was under a threshold value (using five different thresholds from 45 to 65 mg/dl) as quality indicators.
Because for most of the simulated datasets none of the three LR tests were significant, we calculated scores using three different thresholds (i.e. using the first, the first two or the first three principle components), and we took the mean value of the scores for each significant SNP.
We used two different thresholds for differential expression depending on the conditions that were compared, because our analyses showed that lower cutoffs in comparisons of RNA-seq data from microdissected samples and non-microdissected samples resulted in relatively large numbers of false-positives, therefore a more stringent cutoff was used.
DFP for compound data sets with a broad range size (ranging from 100 to 25,000 molecules) were calculated using three different threshold values to explore the fingerprint behavior with respect to database size, diversity, cutoff criteria and different content of information metrics.
