Sentence examples for mean differential expression from inspiring English sources

To date, differential regulation is most often taken to mean differential expression, and a number of useful methods for identifying differentially expressed (DE) genes or gene sets are available.

Most often, differential regulation is taken to mean differential expression; and a number of statistical methods for identifying differentially expressed (DE) genes or gene sets are now available (for reviews, see Allison et al., 2006; Barry et al., 2008; Ho et al., 2007; Newton et al., 2007).

For the binary comparisons of interest, the mean differential expression was calculated for each protein and the statistical significance of the differential expression was established using a two-sided t-test.

To examine if this was a simple linear relationship genes were divided into twelve quantiles based on CpGO/E and mean differential expression was plotted for each quantile.

The 18 genes most consistently separating COO-unclassified DLBCL from either ABC- or GCB-DLBCL are illustrated below with cluster membership and mean differential expression rank shown.

The mean differential expression between good and poor responders for these genes is given in the supplementary information (Additional file 5).

Finally, we compared mean differential gene expression (tumour relative to normal tissue) of whole-genome microarray data from phase I individuals with mean differential gene expression of qRT−PCR data from phase II individuals for the same gene to check for the reliability of the methods employed.

The Pearson's correlation coefficient in the mean differential gene expression estimated by microarray and qPCR was 0.63.

Mean differential gene expression in phase I and phase II data was highly correlated (r=0.86) and had an overall agreement of about 93% (data not shown), supporting the reliability of the methods.

For each disease, here we simply use the mean of differential expression values of subnetwork genes to evaluate the fold change of the disease in the subnetwork genes.

Specifically, we quantify consistency using 'mean gene rank', which is the mean ranked differential expression of a subset of genes, scaled by the number of total genes and offset by 0.5 to set chance = 0. We also determined putative vulnerability and protection genes with AD.