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Statistical significance of the classification was evaluated by comparing the overall accuracy of the 12-gene signature with that of 1000 random signatures of the same size using the same algorithm.
This analysis finds that the number of common Biological Processes (derived without any FDR control) that we found for the real lists was significantly higher than the number for random signatures- we calculated a p-value of 0.015 to get the observed overlap for threshold of p<0.05 (and 0.068 for p<0.1), showing that indeed both signatures capture some common essence.
Therefore, we developed a differential index system using 37,000 random signatures.
Therefore, as a control, we compared the HIS with 1,000 random signatures of identical size and confirmed that the HIS has a much more specific association to patient outcome in this cohort than the best 5% random signatures.
We found that 4.6% of the random signatures were significant (P < 0.05), of which 2% had HR > 1 (Fig 3D).
For these random signatures we obtained a median AUC ~73%, and all had AUCs < 92%, thus giving a p-value < 0.001 for the observed signature.
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The simulation setup used random signature sequences of length 31 and rectangular chip waveforms.
In [8], information capacity of the random signature MIMO CDMA system is calculated.
The CDMA system used here relies on the use of random signature sequences of length 31.
(b) In [8], information capacity of the random signature MIMO CDMA system is calculated.
4. Location in Signature: Allows you to choose to include your location in your signature, using geographical data associated with your public IP address 5. Random Signature: Rotates among random quotes for your signature.
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