12 months ago by
Pathview codes user data (gene expression, metabolite levels etc) in certain range (specified by argument limit) linearly into a continuous color spectrum (specified by arguments low, mid and high). Any value out side the limits will be truncated to the closest limit.The default data limit is (-1, 1), but users can adjust the limits freely based on needs. For example, you may specify limit=c(-3, 3) or even limit=c(-2.5, 4.5) to fit your data. Note that you want to specify informative limits as to best view most (but not necessarily all) of your data.
In KEGG graph, a gene node (or E.C number in your case) may represent multiple genes/proteins with similar or redundant functional role. The number of member genes range from 1 up to several tens. They are intentionally put together as a single node on pathway graphs for better clarity and readability. Therefore, we do not split node and mark each member genes separately by default. But rather we visualize the node-wise data by summarize gene-wise data, users may specify the summarization method using node.sum arguement.
For more information, check the function documentation: