evotec_Nov23_PanOmicsDriven - 36

The PanHunter Platform
problems encountered by other
colleagues. For this purpose,
we often use omics analyses.
PanHunter speeds up and
eases the analysis of these
multi-omics datasets. More
particular, PanHunter comes
with a broad spectrum of tools
to help me to really understand
the mechanisms behind these
unexpected findings.
What are the main points
where PanHunter improved or
accelerated your analysis?
John: The experimental setup
of our multi-omics study is
quite complex. Hence, there
are many different angles
to look at and analyse the
data. I joked that I would
need a post-doc to look at the
data for three years to fully
understand the findings. The
interactivity of PanHunter
makes it very easy for me
dive into, sorting and pulling
out data. My ultimate goal is
to understand the mode-ofaction
of the compounds. It is
very easy to set up differential
analysis in PanHunter. To
analyse the outcomes of
these differential analyses I
started with Euler and Venn
diagrams to understand
differences and similarities
in the mechanisms of the
compounds. Another very
useful tool is the network
visualisation that is based on
BioGRID. This helped me a lot
to identify the proteins that
have physical interactions
with the target protein.
What could you do faster/
better because you had
PanHunter at hand?
John: Definitively the
identification of proteins that
have physical interactions
with the target protein.
As well as the detection of
pathways that are affected
by the compounds. This
helped me a lot to understand
the mechanism behind the
compounds. A thing that
I could do much faster is
the hierarchical clustering
of abundances of proteins/
transcripts based on
predefined features lists.
The predefined feature lists
originate either from public
databases like GO or from
earlier research that I did.
36
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evotec_Nov23_PanOmicsDriven

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