I am trying to look at evolutionary relationships using BI and ML trees. If I have 3 different evolutionary lineages BI gives a node between lineages 1 and 2 (1 and 2 diverged from a common ancestor) whereas ML gives a node between lineages 2 and 3 (2 and 3 diverged from a common ancestor). What could be the possible reasons for this ?
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This is the crux here. OP says nothing about assessing statistical support or how they went from a posterior distribution of trees to a consensus/MCC tree in the Bayesian approaches. If they are high and the topologies disagree, perhaps the dataset is difficult to resolve, there could be methodological bias, or branch lengths are short (among lots of other things).
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