To maximize discovery, E. grandis samples were from BRASUZ1, the same tree whose genome provided the reference sequence.
All three available phylogenetic granularities, strain, species and genus, were used and the results were merged, in order to maximize the discovery rate.
The problem of optimizing such two-stage transcriptional profiling experiments in order to maximize sensitivity, while controlling the false discovery rate (FDR), is addressed.
Furthermore, the analytic methods we used, i.e. LRpath combined with an intensity-based Bayesian moderated t-statistic (IBMT, see the Methods section for details), can maximize the detection power while accurately estimating the false discovery rate, and have also demonstrated superior performance with small sample sizes [ 21, 52].
A two-class unpaired analysis with a false discovery rate (FDR) of 10% was used to maximize sensitivity and minimize the effect on accuracy.
The ideal management of single peptide hits involves maximizing true positive protein identifications while maintaining a strict false discovery rate.
Suitable cutoffs for the GO depth and the Pearson correlation in (iii) and (iv) were determined by maximizing the positive predicted value and the accuracy while minimizing the false discovery rate for 1,000 randomly picked positive pairs as defined by KEGG (see above) and 1,000 random gene pairs or 500 pairs for (iii) and (iv), respectively.
The replication strategy has also been advanced by Zehetmayer et al. [ 15] who "propose multi-stage procedures controlling either the family-wise error rate (FWER) or the false discovery rate (FDR) and derive asymptotically optimal stopping boundaries and sample size allocations (across stages) to maximize the power of the procedure".
The number of genes found at a standard false discovery rate (e.g. 5 %) may then be used as an optimization criterion to be maximized.
