An FC cut-off value of 1 was applied as a threshold criterion.
Nearly 98% of these genes (41 of 42 unique) could not pass the FC cut-off threshold by microarray.
Moreover, using a FC cut-off equal to ± 2, 3724 (13.6%) and 3750 (13.7%) genes were significantly up- and down-regulated in tumors, respectively (see Additional file 2).
Differences in gene expression between wild-type and mutant clones for each patient were calculated using a Fold Change (FC) cut-off of 1.5 and a p<0.05.
The only exception is the gene fliO (XAC1945) that encodes a flagellar protein for flagellum apparatus, which passed the FC cut-off, but failed with FDR threshold.
Because the improvement between a 3-fold and 4-fold FC cut-off was modest in comparison to the improvement between a 2-fold and 3-fold FC cut-off, we decided to consider miRNAs with a ≥3-fold difference as significant in further analyses.
Unlike that of RNA-seq, nearly 63% genes (12 of 19 unique) could pass the FC cut-off threshold, but failed to pass the FDR threshold by RNA-seq.
By using the moderated t-test p value (p) and patient vs control fold change (FC) cut-offs, two gene lists of interest were then generated with different levels of stringency.
To determine the appropriate FC cut-off to use when identifying significantly differentially expressed miRNAs via a fold-change analysis, we examined the consistency of our assay by analyzing a technical repeat of our quantification methods.
The FC cut-off is considered the best indicator of true differential gene expression [ 15, 16] and qPCR validation of Agilent microarray results at a minimum threshold of 1.4 FC has been robust at this specific genomic core [ 17].
To compare matched samples, a fold-change analysis was used (2(case∆Ct - control∆Ct), ∆Ct = Raw endogenous control Ct – Raw assay Ct) and to identify the most significantly deregulated miRNAs a 3-fold change cut-off was applied (selection of fold-change (FC) cut-off explained in results).
