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I have done this manually for my own dataset (character-taxon matrix) and I think the results are really interesting:
Vertices represent individual morphological characters and arrows indicate developmental trajectory. The network is polarised by inclusion of a hypothetical ‘root’ character (note that most cladistic matrices will not have a 'root' character as it would, by definition, be invariant for all taxa). Vertex colour indicates the minimum path distance to the root character. Vertex size is proportional to the number of downstream dependent characters.
Such diagrams are similar to the DDA figures presented in @sergeitarasov's recent preprint.
The text was updated successfully, but these errors were encountered:
That's cool! Nice idea for a project! I am interested. :) There is some old code used in previous SCATE shortcourses to make such dependency graphs for anatomical entities. I think it considers only part_of and is_a relations (not develops_from), but can be something to start with!
Btw, what format do you use to store those ontological relationships? If OWL I would recommend using Owlready2 in python to read the data and query them for plotting?
I have done this manually for my own dataset (character-taxon matrix) and I think the results are really interesting:
Vertices represent individual morphological characters and arrows indicate developmental trajectory. The network is polarised by inclusion of a hypothetical ‘root’ character (note that most cladistic matrices will not have a 'root' character as it would, by definition, be invariant for all taxa). Vertex colour indicates the minimum path distance to the root character. Vertex size is proportional to the number of downstream dependent characters.
Such diagrams are similar to the DDA figures presented in @sergeitarasov's recent preprint.
The text was updated successfully, but these errors were encountered: