Sentence examples for expression patterns were calculated from inspiring English sources
Numbers of those DEGs in the 4 significantly different expression patterns were calculated.
The statistical significance of the resultant expression patterns were calculated as false discovery rates (FDRs) using 1,000 random permutations [ 8].
Genome-wide statistically significant differences in gene expression patterns were calculated using the Wilcoxon Rank Sum Test with Benjamini-Hochberg FDR correction (q < 0.01) in MultiExperiment Viewer (MeV).
Spearman correlation coefficients between global relative expression and individual transcript expression patterns were calculated using Microsoft Excel for each developmental stage, and an average of the four stages is presented.
EST frequency counts for genes with two or more ESTs within one or both of the library sets (singletons were removed) and corresponding differential gene expression patterns were calculated with the IDEG6 web tool using the Audic-Claverie statistic (AC), p-value < 0.01.
Mutual information (MI) between codon usage and expression pattern was calculated in accordance with Najafabadi et al. (2009).
The significance of the association of a motif with a particular expression pattern was calculated using Fisher's Exact Test.
A further case of an antagonistic expression pattern was calculated for MMPs and COL1A1 (rules 21, 30, 36, 41, 54, and 60), for example, in rule 54: <170> SMAD4.on.on, MMP3.out.off, MMP9.out.off, MMP13.out.off,... → COL1A1.out.on Antagonistic expression profiles also can be observed for SMAD4 and other TFs, e.g., JUN and JUNB (rules 12, 39) or ETS1 (rule 15, see above).
The magnitude of the AHP and BLP expression patterns were estimated by calculating the fold change of the hybrid versus the high parent or low parent, respectively.
With the exception of salinity, the environmental data for samples with such highly similar gene expression patterns were also very similar, with calculated pair-wise correlation coefficients in the range of 0.8 0.85 (for all numeric environmental data in Table S1).
