My name is Ron Wehrens. I'm a scientist working
at Wageningen University and Research in the Netherlands.
Today, we're going to talk about the subject of "Univariate Statistics and Metabolomics".
And, I've been doing quite a lot of work in
the past few years on analyzing metabolomics data sets.
The topic of statistics is of central importance to
any field of science where experimental data are being analyzed,
and metabolomics is no exception.
The difficulty in metabolomics comes from two things.
Basically, for every sample that we analyze,
we get a lot of information,
and that is one of the aspects.
And the second thing is that we often don't know what the information means.
So we get signals,
we get peaks from our experimental data,
but we are not exactly sure what these peaks mean and
with which metabolites they are associated.
So the latter part is an annotation problem that I will not go into today.
But what we will try to do is to cover, let's say,
the central ideas behind basic statistical methods
and see how they can be applied in a metabolomics context.