Understanding metabolism is fundamental in biomedical and plant research and the identification and quantification of thousands of metabolites by mass spectrometry in modern metabolomics is a prerequisite for elucidating this area. However, the identification of metabolites is a major bottleneck in traditional approaches hampering advances. Here, we present a novel approach for the untargeted discovery of metabolite families offering a bird's eye view of metabolic regulation in comparative metabolomics. We implemented the presented methodology in the easy-to-use web application MetFamily to enable the analysis of comprehensive metabolomics studies for all researchers worldwide. MetFamily is available under http://msbi.ipb-halle.de/MetFamily/.
There are several issues in the PCA plotting style
1) Annotation in score plot making the plot clumsy
2) Remove the fragmentation plot
3) Display all the Scores selected by the user
4) Remove the fragment stick colors label
5) Remove the cluster-discriminating power label
6) Display full name in the annotation
Just a remark, in the PCA we still have a lingering issue #47 ,
which I looked at before, but I don't have a proper solution yet.
I suggest to check it out together at some stage.
Yours, Steffen
sneumann
commented
3 years ago
There are several issues in the PCA plotting style 1) Annotation in score plot making the plot clumsy 2) Remove the fragmentation plot 3) Display all the Scores selected by the user 4) Remove the fragment stick colors label 5) Remove the cluster-discriminating power label 6) Display full name in the annotation