The IGF2R has a stability value of 0.09 that ranks #52 but the other lower candidates are mostly background (low values). Also looked at the values for the common normalization factors.
| TCTP | 0.145 |
| GAPDH, liver | 0.173 |
| UBC9 | 0.317 |
| PSA-ACT | 0.412 |
TPT1 has a mean of 34915 and SD 4437 and will be quite a bit higher than most proteins in the dataset.
http://cancerres.aacrjournals.org/content/64/15/5245.full
From the paper:
Stability Value.
Having estimated both the intra- and intergroup variation, we combine the two into a stability value, which intuitively adds the two sources of variation and thus represents a practical measure of the systematic error that will be introduced when using the investigated gene.
Let αi be the mean of αig. For a future experiment, it is the distribution of zig − θg − αi that defines the stability of gene i. However, we find a distribution to be an impractical stability measure and therefore reduce it to a one-dimensional value by defining the stability value ρig to be the absolute value of the mean + 1 SD. We use a Bayesian argument to find the distribution of zig − θg − αi in a future experiment (see supplementary data for details). Finally, to implement our stability measure, we need to estimate zig − θg − αi. To this end, we make the assumption that the average of αig over the genes i = 1,… k is independent of the group g. Then zig − θg − αi is naturally estimated by dig = zig − z̄i· − z̄·g + z̄··, where a bar indicates an average, and the stability value becomes
where γ2 is the variance of αig. We estimate γ2 by
if this is positive; otherwise, we set it to 0.
where γ2 is the variance of αig. We estimate γ2 byif this is positive; otherwise, we set it to 0.
To get a single value for gene i, we let ρi be the average of ρig, g = 1,…, G. For details on the derivation and for a stability measure based on an average of several control genes, see the supplementary data.
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