No consensus number was found for the matched contigs between the two libraries using BLASTN in reciprocal searches.
Signature abundance was also compared statistically between the two libraries using a Z-test [ 25], with the resulting statistical significance expressed as a p-value.
Signature frequency was also compared statistically between the two libraries using the Z-score method according to Kal et al. [ 34], which uses the p-value and a statistical significance value.
Signature frequency was also compared statistically between the two libraries using Z-score method according to Kal et al. (1999) [ 41], which use p-value as statistical significance level.
Presence of potential false positives (reported in Table 1) in each subtracted library was assessed by building two local basic local alignment search tool (BLAST) target databases, and evaluating sequence similarities between the two libraries using BLASTN and TBLASTX (Altschul et al. 1997).
We defined differentially-expressed genes by calculating P values between any two libraries using a previously reported statistic method [ 28]; the process yielded 1,751 (8.5%) and 1,216 (5.9%) significant differentially-expressed genes with P values of < 0.05 and < 0.01, respectively (Table 4).
Briefly, p-values were computed to reflect the significance of the difference between two counts (n1 and n2 corresponding to any two library combination out of the six libraries) using a binominal model.
Significance level of the difference of small RNA between two libraries was analyzed using a corrected Z Score method as described in Kal et al., [ 82].
Differentially bound regions (DBRs) were established using the program MAnorm (Shao et al. 2012), which uses common peaks between two libraries (as called by MACS2) to rescale and normalize ChIP data between two treatments, then estimate significance, direction and magnitude of differential ChIP enrichment for all confident ChIP enrichment peaks.
Gene expression difference between any two libraries was determined using IDEG6 software.
