Thank you for your interest. To get a bit more information in order to help you out, can you share the command you used to generate the voila tsv?
As for your question about parsing / filtering your deltapsi (dPSI) output. Roughly E(dPSI) will tell you the expected magnitude of the change between your two groups while P(|dPSI| > threshold) will tell you the probability that a junction in an LSV changed greater than that threshold.
These two are related, but P(|dPSI|>X) > 0.95 would be what we consider a "high-confidence" change (we typically use X=10% or X=20%). This means that 95% of the posterior distribution of dPSI between your compared groups sits beyond your threshold (X) value for dPSI.
LSVs with higher E(dPSI) values will tend to have a higher probability of change, but high read coverage can also drive up this probability higher (we are more sure the dPSI between the groups is "real" (larger than your threshold)). However, a higher probability here does not necessarily mean a larger E(dPSI). With many reads we can be very confident there is a change of at least 20% (P(|dPSI|>20%) ~ 1), without having the highest expected PSI for that LSV (E(dPSI) can be ~20%) out of all LSVs analyzed.
Hopefully this gives you a bit more intuition on how to use these and don't hesitate to ask more questions.