Hey!
I am recently checking out the package and can build graphs from KGML files. I got two queries.
Firstly, I am having trouble understanding the graphs, especially the meaning of the edges. I checked the publication and did not come across a sentence describing the relationship that is portrayed by the edges. Furthermore, I am not understanding the directionality of the edges as well, what do they directions of the arrows mean. Am I missing something?
As for the 2nd question, this is the code I have run:
pathway <- KEGGREST::keggGet("00232", "kgml")
graph <- KEGGgraph::parseKGML2Graph(pathway, genesOnly = T)
plotKEGGgraph(graph, useDisplayName = T)In this particular example, the genes "hsa:1548" and "hsa:1549" are named "CYP2A6" and "CYP2A7" respectively on KEGG website. However, they are both named "CYP2A6" in the graph. I checked the DisplayName by running getKEGGnodeData(graph) and even there it is the same for these genes. This is just 1 gene I am mentioning, but have seen similar behaviour across 3 pathways. It would be lovely if you could check the issue if it is a bug / limitation or something I am doing wrong.
Thank you so much for the wonderful package. Let me know if there are any more info you need.
Best,
Suharto
Hey!
I am recently checking out the package and can build graphs from KGML files. I got two queries.
Firstly, I am having trouble understanding the graphs, especially the meaning of the edges. I checked the publication and did not come across a sentence describing the relationship that is portrayed by the edges. Furthermore, I am not understanding the directionality of the edges as well, what do they directions of the arrows mean. Am I missing something?
As for the 2nd question, this is the code I have run:
In this particular example, the genes "hsa:1548" and "hsa:1549" are named "CYP2A6" and "CYP2A7" respectively on KEGG website. However, they are both named "CYP2A6" in the graph. I checked the DisplayName by running
getKEGGnodeData(graph)and even there it is the same for these genes. This is just 1 gene I am mentioning, but have seen similar behaviour across 3 pathways. It would be lovely if you could check the issue if it is a bug / limitation or something I am doing wrong.Thank you so much for the wonderful package. Let me know if there are any more info you need.
Best,
Suharto