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In this study, genes differentially expressed between two sample groups were selected following the recommendations of the MAQC project [12], [51].
In this list, genes were ranked according to the differential expression between two sample groups.
Differences in BRCA1 expression levels between two sample groups were analysed using the Mann–Whitney U Test.
We used unpaired Student's t test for comparison between two sample groups with a 95%% confidence level.
They generated correlated gene set expression profiles from multivariate normal distributions with no DEG between two sample groups.
Transcriptome maps, showing differential expression between two sample groups, relative to two different biological conditions, may be easily generated.
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Note that this analysis is independent of changes in expression between the two sample groups; it instead detects changes between the groups in correlations found within the groups, and can thus indicate changes in miRNA function in the AD brain.
Hierarchical clustering of complete transcriptional profiling between the two different chip platforms indicated separations between any two sample groups.
Most metabolomic studies a decade ago had a relatively simple experimental design in which the intensities of compounds were compared between only two sample groups.
However, four differences between the two sample groups were found.
The signal with a molecular mass of 10.175 kDa was the most significant single signal capable of discriminating between the two sample groups in this analysis.
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