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Taking gene expression into account, there are no large differences in the distribution of homologues between the genes with largest and smallest gene expression changes.
PCNA had the largest mean gene expression, TP73L had the smallest gene expression and the largest CV, and PTEN had the smallest CV.
The top and bottom 10% of probe sets (1,675) were selected as representing the genes with the largest and smallest gene expression changes in the first 12 hours of differentiation, respectively.
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We conducted a small-scale gene expression analysis in MFS affected subjects.
This permits an accurate estimate of the variance that is used to derive the final p-value and provides confidence in the detection of small gene expression changes.
The advantage is that a limited set of TSRs makes it is possible to analyze even small gene expression datasets with much less danger of false-positive results due to overfitting.
GSEA is predicated on the idea that genes with related biological functions are oftentimes coordinately regulated, and that even small gene expression changes, which escape identification through traditional single gene analysis approaches, are biologically meaningful if in the context of related gene changes [36], [40].
This observation may be due to the relatively small gene expression variation in this data.
To construct these, we simulated a small gene expression dataset under a Normal distribution for 300 genes and 100 samples.
If the classification of samples relies on small gene expression differences, the classification may be microarray format specific.
In this study we observed small gene expression ratios in both microarray and real-time PCR analyses.
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