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Injection time differentials were compared using one-way analysis of variance; post hoc evaluation was performed using the Scheffe test with Bonferroni correction.
After normalization to the shLUC control, cell number differentials were compared over three replicates per cell line for each experiment using a paired Student's t-test.
Complete blood cell count and leukocyte differentials were compared among groups using analysis of variance.Moderated robust regression in the Linear Model for Microarrays (limma) library from bioconductor was used to determine statistically significant miRNAs using a Benjamini Hochberg FDR of 1% [ 29].
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The annotated transcripts (containing ≥2 exons) and orthologues that exhibited differential expression were compared.
The results of the RNA-seq differential analysis were compared with changes in global protein expression using quantitative proteomics.
The patients were separated according to final outcome (dead and alive) and the bone marrow differential counts were compared between the two groups applying t Student test.
The probe sets for each gene in the mutant mice that showed significantly differential expression were compared with those from the strain background matched WT.
Their differential expression patterns were compared among mock-/inoculated- and resistant/susceptible cotton.
Finally, false positive rates of differential miRNA expression were compared to the microarray technique.
Differential expression ratios were compared between platforms to determine the cross-platform correlation.
The accuracy of CodeLink and GeneChip differential-expression ratios were compared to quantitative real-time PCR (qrtPCR).
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