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This test compares means between two samples using their standard deviations.
Student's t-test was used to compare means between two samples using Microsoft Excel.
Referring to "The significance of digital gene expression profiles [ 63]", BGI have developed a strict algorithm to identify differentially expressed genes between two samples using the Poisson model.
We wished to assess the accuracy of a new sense-strand RNA amplification method by comparing ratios between two samples using quantitative real-time PCR (qPCR), mimicking a two-color microarray assay.
The resulting, normalized values were used for a selection of significantly regulated mRNAs, that is, those with an abundance that differed in two or more comparisons between two samples, using a funnel-shaped confidence interval (p < 0.05) calculated from every mRNA detected per hybridisation [ 21].
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These comparisons of the subscale scores between psychiatrists and community members were then repeated after adjusting for differences in gender, age and years of education between the two samples using linear regression methods.
We assess convergence between results from these two samples using two related methods that seek clustering of nominally-positive results and assess significance levels with Monte Carlo and permutation approaches.
This technique compares between the expression profiles of two samples, using hybridization of each sample to oligonucleotide-synthesized labelled probes.
The univariate comparison of the mean scores for the seven subscales between the two samples used t-tests.
The Pearson correlation coefficient was used to determine the significance of the correlation between mRNA datasets of all eight samples using R (version 3.0.0) (http://www.R-project.org) in the FactoMineR package [ 30].
Therefore, we applied a DiffKAP method that allowed us to identify DEGs between two samples without using a reference.
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