Output trees are named: dataset.program.[out].type_of_output_tree.type_of_input.tree Possible values for type_of_output_tree and type_of_input vary by program. For example, ASTRAL outputs trees with bootstrap support or posterior probabilities so these are two possible types of output trees. ASTRAL can also accept ML trees or ML trees with low-supported nodes collapsed, so these are two possible types of input trees. If paramters were varied across runs, that's noted in the file name (only relevant for SVDQ). The total trees for each program are: ASTRAL: 3 datasets x 2 input trees x 2 output trees = 12 ASTRAL trees MP-EST: 3 datasetes x 1 input tree x 1 output tree = 3 MP-EST trees STAR: 3 datasetes x 1 input tree x 1 output tree = 3 MP-EST trees SVDQ: 2 datasets (svdq and alleles) x 1 output tree = 2 + 2 datasets (iupac and default) x 2 handling of ambiguities (missing or distributed) x 1 output tree = 4 =6 SVDQ trees RAxML (CAML trees) 2 datasets x 1 output tree = 2 RAxML trees Total trees: 26