Hi, > Would it make sense to do the following: for each community, get all the > functional scores for of all its interacting pairs. Then get the same > number of interacting pairs observed in the community, but at random > from the network. The run a Mann–Whitney U between the two vectors of > scores.
How about this one: get all the functional scores for all the interacting pairs _within_ the community, then get the functional scores for all the interacting pairs for which one member is within the community and the other is outside, and then run a Mann-Whitney U-test on these two vectors? (Don't forget to apply some kind of multiple hypothesis testing correction if you wish to derive a significance metric for the _entire_ clustering instead of the significance of _separate_ communities). Best, T. _______________________________________________ igraph-help mailing list [email protected] https://lists.nongnu.org/mailman/listinfo/igraph-help
