I am studying q2-mmvec to analyze my data( metabolome and the microbiom). However, I meet some questions about input files.
Firstly, I have gained a table of microbe’s taxonomy via USEARCH, and there is not ‘confidence’ in this table(maybe I have ignored some details).But in sample data of mmvec(cf/taxonomy.txt) has ‘confidence’. Therefore, I wonder if the ‘confidence’ is necessary for mmvec ?
Secondly, my original data about metabolome mainly has sample ID, compounds’ name and different compounds abundances in different samples, and I have poorly understood how to gain metabolite-metadata in sample data of mmvec (‘cf/metabolite-metadata.txt’). In other words, I don’t know what information metabolite-metadata needs and how to let my data of metabolome convert this format, probably I have ignored some steps.
Looking forward to your reply. Thank you!
confidence shouldn’t be necessary as long as it is a qiime2 compatible FeatureData[Sequence] type.
if you don’t have any additional metabolite information, you could just feed in a file with all of the compound names again. Normally, this metabolite information is accommodated with m/z, retention time, in addition to other annotations from classyfire or sirius, or even KEGG.
Hi mortonjt !
Because there is not ‘Compound_Source’ in my metabolite metadata, I have substituted 'Class II' or 'Class I' for 'Compound Source', and my metabolite metadata is shown in the following table.
sampleID
Q1 (Da)
Q3 (Da)
Molecular Weight (Da)
Formula
Ionization model
Compounds
Class I
Class II
CAS
Level
cpd_ID
kegg_map
2268
138.05
94.07
137.048
C7H7NO2
[M+H]+
Trigonelline
Alkaloids
Alkaloids
535-83-1
B
C01004
ko00760
But when I run 'qiime mmvec heatmap' with 'Class I' or 'Class II', my heatmap was a little messy. A part of heatmap is shown in following picture.
I tried to normalize my heatmap by using PDF editing or transferring PDF to PPT, but they didn't work. So I have no idea to normalize it.
Looking forward your reply!
I’m sorry I didn’t express very clearly. The picture I show is just a problematic part of complete heatmap. And my problem is that the layout of my heat map is a bit confusing( some text and graphics are overlapped together ), I think it should be as you have said that the colormap is a bit off. And this question is more obvious when ‘Class_II’ replaces ‘Compound_source’( I’ve highlighted the problem in the picture).
hmm yes I see what you mean. MMvec is not a great plotting library for this reason. Getting labels to fit is a hard problem; and we are probably not going to be able to fix it in a completely automated fashion.
There are 2 workarounds to this problem
You manipulate the image in Photoshop / Inkscape, or some other image manipulation package. The pdf should have vectorized elements that you can manipulate by hand.
You can replot everything in Python / R. If you are comfortable with Python, you can directly manipulate the seaborn object that is used to generate this visualization. You’d just need to run the ranks_heatmap function.
