![](bg7.png)
B Protein levels of RPS3 and ENP1 (as a loading
control) derived from experiment shown in A were
detected by Western blotting. Note that si-DTNBP1-
2 reduces RPS3 levels.
4 CONCLUSIONS
The major objective of this paper was to describe a
new algorithm and software toolkit to analyse off-
target effects in RNAi screening data.
The test and validation phase has proven that the
software already provides a powerful and flexible
toolkit for analysing off-target effects. Testing and
validating the toolkit with an actual high content
dataset revealed that the workflow environment is
suitable for off-target analysis. The analyses of the
given dataset show that the environment allows for a
dynamic workflow adaption based on intermediate
results, e.g. by supplemental Text Filter integration.
In addition to the flexible workflow creation facility,
the individual configuration options of a single node
are also advantageous. All in all, the software
environment with its flexibility turns out to be very
suitable to analyse off-target effects in RNAi
screening data. An important aspect is the reliability
of the results obtained in the analysis process. In this
case the results seem to be reasonable and correct.
We would like emphasize that our predictions
neither include the effects of siRNA concentration
nor do they attempt to account for the siRNA pool
constructs. It is clear that both these effects are of
critical practical consequence and that a
computational model supporting them is desirable.
At the moment, however, there is insufficient
published data on the efficacies of pools to be able
to construct a high-confidence model of pool effects.
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