However, reconstructing the full ancestral (pre-duplication) target set from our dataset is not possible.
A direct comparison of the performance of these platforms with our dataset is not possible due to the differences in target region, sequencing and analysis strategy.
Direct computation of this quantity for real datasets is not possible, because the true breeding value is unknown.
Given the size limitations of the available dataset, it was not possible for the moderate/severe class to be separated into two, such that this hypothesis could be tested; this is left for future investigation.
This will result in more extreme interaction effects; however, due to a limited number of individuals in our dataset, this was not possible in this study.
Misclassifications were identified using local knowledge and addressed in the automation process, but given the national-level coverage of the dataset it was not possible to correct all minor inconsistencies.
Because of the wide spectrum of experimental systems, conditions, laboratories, and array platforms represented among all of the profile datasets, it was not possible to analyze all of the datasets in the same way and to use a single p-value cut off (e.g. p<0.01 for each comparison).
For a small number of datasets, it was not possible to obtain raw data for analysis.
The relationship between ePPID and protein evolutionary rate is also robustly significant in all protein interaction datasets, which was not possible when using PPID in previous studies.
Even with a large sample size across multiple trauma datasets, it was not possible to develop a transportable and clinically useful prediction model based on available admission parameters.
