The cladogram can also come from the literature. They are then usually based on a different set of characters than we ourselves have available. In that case we apply a user-tree evaluation as a tool for comparing the effect of different data sets.
Another possible use of user-tree evaluation may result from running a primary analysis on a data matrix containing the 'better' characters that, however, do not give a completely resolved cladogram. After saving, this cladogram can be entered as a user-tree and evaluated against another data matrix containing the 'weaker' characters, and consequently subjected to a secondary analysis on the basis of the 'weaker' characters.
User-tree evaluation can also be applied in the study of coevolution for those cases where independent cladograms are available for hosts and parasites (or genes and taxa: molecular vs morphological data).
User-trees must be available as ASCII (TEXT) files, either in parentheses format (in CAFCA spaces instead of commas are allowed, but the closing semicolon must be present), or as a binary matrix with the tree topology presented in additive binary coding (see example below).
We can also copy a cladogram matrix from a CAFCA OutputFile to use as a user-tree. Such a cladogram already has the format of a binary matrix.
On the other hand, it may also be very likely that you use PAUP 3.0 for the Macintosh to run your phylogenetic analyses, but that occasionally you get more than one most parsimonious tree and you want CAFCA to calculate the Redundancy Quotients for these trees. In that case youto in by means of the PAUP menu and you your (include a translation table, but leave out any comments) by means of the PAUP menu. Table 5.1 shows an example of the Second data matrix, and the tree file as exported by PAUP, ready to be used in a user-tree evaluation by CAFCA.
Aus 10000110011 Bus 10000110110 Cus 01000001100 Dus 01001001100 Eus 00100000100 Fus 00010100111 Gus 00010100001 Hus 00010110010 Ius 00101000110 Anc 00000000000 #NEXUS begin trees; [Treefile saved Monday, June 8, 1992 6:04 PM] [!Heuristic search settings: 1 tree(s) held at each step during stepwise addition Tree-bisection-reconnection (TBR) branch-swapping performed MULPARS option in effect Steepest descent option not in effect Initial MAXTREES setting = 100 Branches having maximum length zero collapsed to yield polytomies Topological constraints not enforced Trees are rooted Total number of rearrangements tried = 968 Length of shortest tree found = 18 Number of trees retained = 3 Time used = 1.12 sec ] translate 1 Aus, 2 Bus, 3 Cus, 4 Dus, 5 Eus, 6 Fus, 7 Gus, 8 Hus, 9 Ius, 10 Anc ; tree PAUP_1 = ((((1,2),((6,7),8)),((3,4),(5,9))),10); tree PAUP_2 = (((((1,2),8),(6,7)),((3,4),(5,9))),10); tree PAUP_3 = ((((((1,2),8),6),7),((3,4),(5,9))),10); endblock;
Table 5.1 Example of a data matrix asby PAUP (top) and a tree file (bottom) resulting from a operation in PAUP, both based on the data matrix as used in chapter 4 on secondary analyses in CAFCA.
Clickfor the default value ( ).
When the evaluation of the user-tree is finished, READY will appear on the screen. You can now print the results.
As a data matrix etc.. is present in the workspace, CAFCA can not know whether you want to print the results of a primary analysis you could have been running, or the results of a user-tree evaluation. Clickfor ( in the next dialog.
Selection criteria for cladograms of: SecondEvaltree Column numbers refer to numbers of cladograms --------------------------------------------- Row 1 : Total number of homoplasous events Row 2 : Total number of single origins (Support) Row 3 : Corrected Extra Length (x1000; CEL: Turner + Zandee) Row 4 : Total number of state changes (S: Steps) Row 5 : Redundancy Quotient (x1000; RQ: Zandee + Geesink) Row 6 : Rescaled Redundancy Quotient (x1000; RQc) Row 7 : Consistency Index (x1000; CI), with autapomorphy correction Row 8 : Rescaled Consistency Index (x1000; RC: Farris) Row 9 : Average Unit Character Consistency (x1000; AUCC: Sang) Row 10: Homoplasy Distribution Ratio (x1000; HDR: Sang) Row 11: Compatible Character State Index (x1000; CCSI: Zandee) 1 2 3 ------------------ 1 | 6 6 6 2 | 7 7 7 3 | 7197 7197 7220 4 | 18 18 18 5 | 521 521 512 6 | 147 147 133 7 | 611 611 611 8 | 417 417 417 9 | 742 742 742 10 | 338 338 338 11 | 273 273 273 No-Order Limit for Steps, Extra Steps, RQ, and CI: S ES RQ CI ------------------- 33 22 438 333
Table 5.2: Result of the evaluation of the user-trees from the file
Looking at the result of the cladogram evaluation listed in table 5.2 we notice that cladograms number 1 and 2 (fig 5.1) have the highest value of RQ and the lowest for CEL. Comparing this result with that obtained in the secondary analyses we also notice that all cladograms from the PAUP analysis are among the cladograms generated by CAFCA in its primary and secondary analyses on the same data matrix, as shown in chapter 5. PAUP, however, finds these different most parsimonious solutions very quickly and direct (contrary to the indirect nature of the secondary analysis by CAFCA) with either the branch & bound or the exhaustive search option.
Figure 5.1. Two cladograms from PAUP analysis on Second, used as user-trees, with highest RQ.
© M. Zandee 1996.