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Although users often focus on a cutoff score that achieves a balance between sensitivity and specificity, more liberal cutoffs for screening purposes versus conservative cutoffs when cost or risk of further evaluation is deemed to be high should also be considered.
We chose liberal cutoffs for filtering the probesets, because we wanted to maximize the number of probesets in each gene expression array study available for downstream analysis.
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A CSIDR cutoff of ≈24 achieved the best balance between sensitivity and specificity, whereas a more liberal cutoff score of ≈19 resulted in higher sensitivity while maintaining respectable specificity which may be preferred for screening purposes.
Although Rutkowski and Svetina (2014) proposed more liberal cutoff values to evaluate change in model fit for large-scale data analyses, these differences are mainly justified with the larger number of groups (i.e., countries).
Despite evidence for multiple recruiters, over 40% of Tup1 genomic targets were not bound by a known recruiter, even when using a relatively liberal cutoff (P<0.01).
Additionally, jMOTU avoids carrying out an all-against-all pairwise alignment by taking advantage of the fact that the clustering algorithm only requires exact distances between pairs of sequences that are relatively similar (i.e. those that will be clustered together under the most liberal cutoff).
We retain all BLASTX hits with an E-value lower than 10, a very liberal cutoff.
In this study a liberal cutoff was chosen (outside of 1.5SD's).
3. The authors utilize a liberal cutoff in their identification of differentially expressed genes from their microarray analysis.
A threshold of MA = 1.5, corresponding to a p-value of ~0.1, was chosen as a liberal cutoff value to identify differentially expressed gene modules.
Notably, the relatively low numbers of PT-differentially regulated genes compared to those of PP may have occurred, despite taking a liberal cutoff (2 fold).
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