I have assigned KO numbers to my assembled transcriptome and would like to generate a KEGG pathway classification with x axis show gene numbers and percentage for each different terms. There seems exist a standard format for the chart that people use for publication. I would like to know the tool they use to make
this chart.
Thank you
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dongchenchen •
I like clusterProfiler for this task, it provides fairly straightforward integration of both KEGG Pathway Enrichment Analysis as well as visualizations
I don't know any tool that directly provides such chart, but that looks like base R plot to me.
Maybe people use KEGG mapper tool, like this one : https://www.genome.jp/kegg/tool/map_pathway.html
then format the results to be imported in R and use the barplot function https://www.statmethods.net/graphs/bar.html
This graph could definitely be generated using grouped bar plot in R (ggplot2).
To get the KEGG Pathways and their corresponding values, you should run KEGG reconstruction (https://www.genome.jp/kegg/tool/map_pathway.html) using your KOs. Format the resulting file to a table that will be used in R to generate the desired graph.
Hi! How can I download the results from KEGG mapper and format it for plotting it in R.
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Hi @dongchenchen, was wondering if you were able to crack the R-code for this KEGG pathway classification chart. Pls post it here in case you were able to make one Thanks!
Hi, I think python package might help to draw such like of image.
Yes. I was able to generate the graph live above. For the plotting part, Excel is enough. ggplot for R or Matplotlib for Python would do fair job as well. My initial difficulty was to prepare data ready to generate graph from the raw annotation exported from KEGG website. I wrote a python script to group the annotation result in desired level (B level in my case). And then did the counting after uniquely sorted them.
If you don't mind, share your details working script here!
Thanks
Has anyone been able to create the script for this annotation of the hierarchies?
In case when multiple genome sequences used.. how to interprete the data from KEGG plot and COG plot?