In order to avoid this problem, a less restrictive threshold, i.e., μglobal, is used instead.
If looking for possible gene targets of transcription factors, it is advisable to use less restrictive threshold, resulting in more false positives but fewer false negatives.
In a typical analysis of high-throughput gene expression data, the choice of false discovery rate (FDR) threshold is not objective, i.e., it represents an arbitrary balance between missing relevant genes due to a highly restrictive threshold, and a less restrictive threshold resulting in an increasing number of differentially-expressed genes with more false positives.
Under less restrictive probability thresholds designed to minimize the detection of hybrids, the total proportion of hybrids in the transect decreased by only 5%.
In contrast, pooled data including trials with less restrictive transfusion thresholds did not show associations with any of the predefined outcomes.
Of these two very comparable options, we tentatively opted for the less restrictive criterion (threshold 14 or more) to increase the likelihood of identifying successful NFT candidates.
Because CAFE uses mRNA expression as a surrogate for DNA copy number and because the levels of mRNA expression are variable and do not strictly reflect DNA copy number, a less restrictive default threshold is recommended as a starting point for analysis: ±log2(1.5) ratio.
However, for severe epidemics, lower compliance (50%70%%) and the 0-case threshold used more strategy time than less restrictive ending case thresholds.
What was surprising was that these trends were observed even at less restrictive E-value thresholds, where it might be expected that proteins of lower similarity, and thus more likely to be false positives, would presumably be added to the network.
When further evidences were needed to corroborate dubious synteny connections between genes, sequence clustering was performed at a less restrictive e-value threshold (E-15).
