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3<HEAD>
4<TITLE>penny</TITLE>
5<META NAME="description" CONTENT="penny">
6<META NAME="keywords" CONTENT="penny">
7<META NAME="resource-type" CONTENT="document">
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12<DIV ALIGN=RIGHT>
13version 3.6
14</DIV>
15<P>
16<DIV ALIGN=CENTER>
17<H1>PENNY - Branch and bound to find<BR>all most parsimonious trees</H1>
18</DIV>
19<P>
20&#169; Copyright 1986-2002 by the University of
21Washington.  Written by Joseph Felsenstein.  Permission is granted to copy
22this document provided that no fee is charged for it and that this copyright
23notice is not removed.
24<P>
25PENNY is a program that will find all of the most parsimonious trees
26implied by your data.  It does so not by examining all possible trees,
27but by using the more sophisticated "branch and bound" algorithm, a
28standard computer science search strategy first applied to
29phylogenetic inference by Hendy and Penny (1982).  (J. S. Farris
30[personal communication, 1975] had also suggested that this strategy,
31which is well-known in computer science, might
32be applied to phylogenies, but he did not publish this suggestion).
33<P>
34There is, however, a price to be paid for the certainty that one has
35found all members of the set of most parsimonious trees.  The problem of
36finding these has been shown (Graham and Foulds, 1982; Day, 1983) to be
37NP-complete, which is equivalent to saying that there is no
38fast algorithm that is guaranteed to solve the problem in all cases
39(for a discussion of NP-completeness, see the Scientific American
40article by Lewis and Papadimitriou, 1978).  The result is that this
41program, despite its algorithmic sophistication, is VERY SLOW.
42<P>
43The program should be slower than the other tree-building programs
44in the package, but useable up to about ten species.  Above this it will
45bog down rapidly, but exactly when depends on the data and on how much
46computer time you have (it may be more effective in the hands of someone
47who can let a microcomputer grind all night than for someone who
48has the "benefit" of paying for time on the campus mainframe computer).  IT
49IS VERY IMPORTANT FOR YOU TO GET A FEEL FOR HOW LONG THE PROGRAM
50WILL TAKE ON YOUR DATA.  This can be done by running it on subsets
51of the species, increasing the number of species in the run until you
52either are able to treat the full data set or know that the program
53will take unacceptably long on it.  (Making a plot of the logarithm of run
54time against species number may help to project run times).
55<P>
56<H2>The Algorithm</H2>
57<P>
58The search strategy used by PENNY starts by making a tree consisting of the
59first two species (the first three if the tree is to be unrooted).  Then
60it tries to add the next species in all possible places (there are three
61of these).  For each of the resulting trees it evaluates the number of
62steps.  It adds the next species to each of these, again in all
63possible spaces.  If this process would continue it would simply
64generate all possible trees, of which there are a very large number even
65when the number of species is moderate (34,459,425 with 10 species).  Actually
66it does not do this, because the trees are generated in a
67particular order and some of them are never generated.
68<P>
69Actually the order in which trees are generated is not quite as
70implied above, but is a "depth-first search".  This
71means that first one adds the third species in the first possible
72place, then the fourth species in its first possible place, then
73the fifth and so on until the first possible tree has been produced.  Its
74number of steps is evaluated.  Then one "backtracks" by trying the
75alternative placements of the last species.  When these are exhausted
76one tries the next placement of the next-to-last species.  The
77order of placement in a depth-first search is like this for a
78four-species case (parentheses enclose monophyletic groups):
79<P>
80&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Make tree of first two species&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;(A,B)<BR>
81&nbsp;&nbsp;&nbsp;&nbsp;&nbsp&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Add C in first place&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;((A,B),C)<BR>
82&nbsp;&nbsp;&nbsp;&nbsp;&nbsp&nbsp;&nbsp;&nbsp;&nbsp;&nbsp&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Add D in first place&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;(((A,D),B),C)<BR>
83&nbsp;&nbsp;&nbsp;&nbsp;&nbsp&nbsp;&nbsp;&nbsp;&nbsp;&nbsp&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Add D in second place&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;((A,(B,D)),C)<BR>
84&nbsp;&nbsp;&nbsp;&nbsp;&nbsp&nbsp;&nbsp;&nbsp;&nbsp;&nbsp&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Add D in third place&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;(((A,B),D),C)<BR>
85&nbsp;&nbsp;&nbsp;&nbsp;&nbsp&nbsp;&nbsp;&nbsp;&nbsp;&nbsp&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Add D in fourth place&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;((A,B),(C,D))<BR>
86&nbsp;&nbsp;&nbsp;&nbsp;&nbsp&nbsp;&nbsp;&nbsp;&nbsp;&nbsp&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Add D in fifth place&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;(((A,B),C),D)<BR>
87&nbsp;&nbsp;&nbsp;&nbsp;&nbsp&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Add C in second place: ((A,C),B)<BR>
88&nbsp;&nbsp;&nbsp;&nbsp;&nbsp&nbsp;&nbsp;&nbsp;&nbsp;&nbsp&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Add D in first place&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;(((A,D),C),B)<BR>
89&nbsp;&nbsp;&nbsp;&nbsp;&nbsp&nbsp;&nbsp;&nbsp;&nbsp;&nbsp&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Add D in second place&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;((A,(C,D)),B)<BR>
90&nbsp;&nbsp;&nbsp;&nbsp;&nbsp&nbsp;&nbsp;&nbsp;&nbsp;&nbsp&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Add D in third place&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;(((A,C),D),B)<BR>
91&nbsp;&nbsp;&nbsp;&nbsp;&nbsp&nbsp;&nbsp;&nbsp;&nbsp;&nbsp&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Add D in fourth place&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;((A,C),(B,D))<BR>
92&nbsp;&nbsp;&nbsp;&nbsp;&nbsp&nbsp;&nbsp;&nbsp;&nbsp;&nbsp&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Add D in fifth place&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;(((A,C),B),D)<BR>
93&nbsp;&nbsp;&nbsp;&nbsp;&nbsp&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Add C in third place&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;(A,(B,C))<BR>
94&nbsp;&nbsp;&nbsp;&nbsp;&nbsp&nbsp;&nbsp;&nbsp;&nbsp;&nbsp&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Add D in first place&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;((A,D),(B,C))<BR>
95&nbsp;&nbsp;&nbsp;&nbsp;&nbsp&nbsp;&nbsp;&nbsp;&nbsp;&nbsp&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Add D in second place&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;(A,((B,D),C))<BR>
96&nbsp;&nbsp;&nbsp;&nbsp;&nbsp&nbsp;&nbsp;&nbsp;&nbsp;&nbsp&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Add D in third place&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;(A,(B,(C,D)))<BR>
97&nbsp;&nbsp;&nbsp;&nbsp;&nbsp&nbsp;&nbsp;&nbsp;&nbsp;&nbsp&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Add D in fourth place&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;(A,((B,C),D))<BR>
98&nbsp;&nbsp;&nbsp;&nbsp;&nbsp&nbsp;&nbsp;&nbsp;&nbsp;&nbsp&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Add D in fifth place&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;((A,(B,C)),D)<BR>
99<P>
100Among these fifteen trees you will find all of the four-species
101rooted bifurcating trees, each exactly once (the parentheses each enclose
102a monophyletic group).  As displayed above, the backtracking
103depth-first search algorithm is just another way of producing all
104possible trees one at a time.  The branch and bound algorithm
105consists of this with one change.  As each tree is constructed,
106including the partial trees such as (A,(B,C)), its number of steps
107is evaluated.  In addition a prediction is made as to how many
108steps will be added, at a minimum, as further species are added.
109<P>
110This is done by counting how many binary characters which are invariant in the
111data up the species most recently added will ultimately show variation when
112further species
113are added.  Thus if 20 characters vary among species A, B, and C and their
114root, and if tree ((A,C),B) requires 24 steps, then if there are 8 more
115characters which will be seen to vary when species D is added, we can
116immediately say that no matter how we add D, the resulting tree can have no less
117than 24 + 8 = 32 steps.  The point of all this is that if a previously-found
118tree such as ((A,B),(C,D)) required only 30 steps, then we know that
119there is no point in even trying to add D to ((A,C),B).  We have
120computed the bound that enables us to cut off a whole line of inquiry
121(in this case five trees) and avoid going down that particular branch
122any farther.
123<P>
124The branch-and-bound algorithm thus allows us to find all most parsimonious
125trees without generating all possible trees.  How much of a saving this
126is depends strongly on the data.  For very clean (nearly "Hennigian")
127data, it saves much time, but on very messy data it will still take
128a very long time. 
129<P>
130The algorithm in the program differs from the one outlined here
131in some essential details: it investigates possibilities in the
132order of their apparent promise.  This applies to the order of addition
133of species, and to the places where they are added to the tree.  After
134the first two-species tree is constructed, the program tries adding
135each of the remaining species in turn, each in the best possible place it
136can find.  Whichever of those species adds (at a minimum) the most
137additional steps is taken to be the one to be added next to the tree.  When
138it is added, it is added in turn to places which cause the fewest
139additional steps to be added.  This sounds a bit complex, but it is done
140with the intention of eliminating regions of the search of all possible
141trees as soon as possible, and lowering the bound on tree length as quickly
142as possible.
143<P>
144The program keeps a list of all the most parsimonious
145trees found so far.  Whenever
146it finds one that has fewer steps than
147these, it clears out the list and
148restarts the list with that tree.  In the process the bound tightens and
149fewer possibilities need be investigated.  At the end the list contains
150all the shortest trees.  These are then printed out.  It should be
151mentioned that the program CLIQUE for finding all largest cliques
152also works by branch-and-bound.  Both problems are NP-complete but for
153some reason CLIQUE runs far faster.  Although their worst-case behavior
154is bad for both programs, those worst cases occur far more frequently
155in parsimony problems than in compatibility problems.
156<P>
157<H2>Controlling Run Times</H2>
158<P>
159Among the quantities available to be set at the
160beginning of a run of PENNY, two (howoften and howmany) are of particular
161importance.  As PENNY goes along it will keep count of how many
162trees it has examined.  Suppose that howoften is 100 and howmany is 1000,
163the default settings.  Every time 100 trees have been examined, PENNY
164will print out a line saying how many multiples of 100 trees have now been
165examined, how many steps the most parsimonious tree found so far has,
166how many trees of with that number of steps have been found, and a very
167rough estimate of what fraction of all trees have been looked at so far.
168<P>
169When the number of these multiples printed out reaches the number howmany
170(say 1000), the whole algorithm aborts and prints out that it has not
171found all most parsimonious trees, but prints out what is has got so far
172anyway.  These trees need not be any of the most parsimonious trees: they are
173simply the most parsimonious ones found so far.  By setting the product
174(howoften times howmany) large you can make
175the algorithm less likely to abort, but then you risk getting bogged
176down in a gigantic computation.  You should adjust these constants so that
177the program cannot go beyond examining the number of trees you are reasonably
178willing to wait for.  In their initial setting the program will
179abort after looking at 100,000 trees.  Obviously you may want to adjust
180howoften in order to get more or fewer lines of intermediate notice of how
181many trees have been looked at so far.  Of course, in small cases you may
182never even reach the first multiple of howoften and nothing will be printed out
183except some headings and then the final trees.
184<P>
185The indication of the approximate percentage of trees searched so far will
186be helpful in judging how much farther you would have to go to get the full
187search.  Actually, since that fraction is the fraction of the set of all
188possible trees searched or ruled out so far, and since the search becomes
189progressively more efficient, the approximate fraction printed out will
190usually be an underestimate of how far along the program is, sometimes a
191serious underestimate.
192<P>
193A constant that affects the result is
194"maxtrees", which controls the
195maximum number of trees that can be stored.  Thus if
196"maxtrees" is 25, and 32 most parsimonious trees are found,
197only the first 25 of these are stored and printed out.  If "maxtrees"
198is increased, the program does not run any slower but requires a little
199more intermediate storage space.  I recommend that
200"maxtrees" be kept as large as you can, provided you are willing to
201look at an output with that many trees on it!  Initially,
202"maxtrees" is set to 100 in the distribution copy.
203<P>
204<H2>Methods and Options</H2>
205<P>
206The counting of the length of trees is done by an algorithm nearly
207identical to the corresponding algorithms in MIX, and thus the remainder
208of this document will be nearly identical to the MIX document.  MIX
209is a general parsimony program which carries out the Wagner and
210Camin-Sokal parsimony methods in mixture, where each character can have
211its method specified.  The program defaults to carrying out Wagner
212parsimony.
213<P>
214The Camin-Sokal parsimony method explains the data by assuming that
215changes 0 --> 1 are allowed but not changes 1 --> 0.  Wagner parsimony
216allows both kinds of changes.  (This under the assumption that 0 is the
217ancestral state, though the program allows reassignment of the ancestral
218state, in which case we must reverse the state numbers 0 and 1
219throughout this discussion).  The criterion is to find the tree which
220requires the minimum number of changes.  The Camin-Sokal method is due
221to Camin and Sokal (1965) and the Wagner method to Eck and Dayhoff
222(1966) and to Kluge and Farris (1969).
223<P>
224Here are the assumptions of these two methods:
225<P>
226<OL>
227<LI>Ancestral states are known (Camin-Sokal) or unknown (Wagner).
228<LI>Different characters evolve independently.
229<LI>Different lineages evolve independently.
230<LI>Changes 0 --> 1 are much more probable than changes 1 --> 0
231(Camin-Sokal) or equally probable (Wagner).
232<LI>Both of these kinds of changes are a priori improbable over the
233evolutionary time spans involved in the differentiation of the
234group in question.
235<LI>Other kinds of evolutionary event such as retention of polymorphism
236are far less probable than 0 --> 1 changes.
237<LI>Rates of evolution in different lineages are sufficiently low that
238two changes in a long segment of the tree are far less probable
239than one change in a short segment.
240</OL>
241<P>
242That these are the assumptions of parsimony methods has been documented
243in a series of papers of mine: (1973a, 1978b, 1979, 1981b,
2441983b, 1988b).  For an opposing view arguing that the parsimony methods
245make no substantive
246assumptions such as these, see the papers by Farris (1983) and Sober (1983a,
2471983b), but also read the exchange between Felsenstein and Sober (1986). 
248<P>
249The input for PENNY is the standard input for discrete characters
250programs, described above in the documentation file for the
251discrete-characters programs.  States "?", "P", and "B" are allowed.
252<P>
253Most of the options are selected using a menu:
254<P>
255<TABLE><TR><TD BGCOLOR=white>
256<PRE>
257
258Penny algorithm, version 3.6a3
259 branch-and-bound to find all most parsimonious trees
260
261Settings for this run:
262  X                     Use Mixed method?  No
263  P                     Parsimony method?  Wagner
264  F        How often to report, in trees:  100
265  H        How many groups of  100 trees:  1000
266  O                        Outgroup root?  No, use as outgroup species  1
267  S           Branch and bound is simple?  Yes
268  T              Use Threshold parsimony?  No, use ordinary parsimony
269  A   Use ancestral states in input file?  No
270  W                       Sites weighted?  No
271  M           Analyze multiple data sets?  No
272  0   Terminal type (IBM PC, ANSI, none)?  (none)
273  1    Print out the data at start of run  No
274  2  Print indications of progress of run  Yes
275  3                        Print out tree  Yes
276  4     Print out steps in each character  No
277  5     Print states at all nodes of tree  No
278  6       Write out trees onto tree file?  Yes
279
280Are these settings correct? (type Y or the letter for one to change)
281</PRE>
282</TD></TR></TABLE>
283<P>
284The options X, O, T, A, and M are the usual Mixed Methods, Outgroup,
285Threshold, Ancestral
286States, and Multiple Data Sets options.  They are described in the Main
287documentation file and in the Discrete Characters Programs documentation
288file.  The O option is only acted upon if the final tree is unrooted.
289<P>
290The option P toggles between the Camin-Sokal parsimony criterion
291and the Wagner parsimony criterion.  Options F and H reset the
292variables howoften (F) and howmany (H).  The user is prompted for the new
293values.  By setting these larger the program will report its progress less
294often (howoften) and will run longer (howmany times howoften).  These values
295default to 100 and 1000 which
296guarantees a search of 100,000 trees, but these can be changed.  Note that
297option F in this program is not the Factors option available in some of
298the other programs in this section of the package.
299<P>
300The A (Ancestral states) option works in the usual way, described in the
301Discrete Characters Programs documentation file.  If
302the A option is not used, then the program will assume 0 as the
303ancestral state for those characters following the Camin-Sokal method,
304and will assume that the ancestral state is unknown for those characters
305following Wagner parsimony.  If any characters have unknown ancestral
306states, and if the resulting tree is rooted (even by outgroup),
307a table will be printed out
308showing the best guesses of which are the ancestral states in each
309character.
310<P>
311The S (Simple) option alters a step in PENNY which reconsiders the
312order in which species are added to the tree.  Normally the decision as to
313what species to add to the tree next is made as the first tree is being
314constructed; that ordering of species is not altered subsequently.  The
315S option causes it to be continually reconsidered.  This will probably
316result in a substantial increase in run time, but on some data sets of
317intermediate messiness it may help.  It is included in case it might prove
318of use on some data sets.
319<P>
320The F (Factors)
321option is not available in this program, as it would have no effect on
322the result even if that information were provided in the input file.
323<P>
324The final output is standard: a set of trees, which
325will be printed as rooted or unrooted
326depending on which is appropriate, and if the user elects to see them,
327tables of the number of changes
328of state required in each character.  If the Wagner option is in force for a
329character, it may not be possible to unambiguously locate the places on
330the tree where the changes occur, as there may be multiple possibilities.  A
331table is available to be printed out after each tree, showing for each branch
332whether
333there are known to be changes in the branch, and what the states are inferred
334to have been at the top end of the branch.  If the inferred state is a "?"
335there will be multiple equally-parsimonious assignments of states; the user
336must work these out for themselves by hand.
337<P>
338If the Camin-Sokal parsimony method (option C or S)
339is invoked and the A option is also used, then the program will
340infer, for any character whose ancestral state is unknown ("?") whether the
341ancestral state 0 or 1 will give the fewest state changes.  If these are
342tied, then it may not be possible for the program to infer the
343state in the internal nodes, and these will all be printed as ".".  If this
344has happened and you want to know more about the states at the internal
345nodes, you will find helpful to use MOVE to display the tree and examine
346its interior states, as the algorithm in MOVE shows all that can be known
347in this case about the interior states, including where there is and is not
348amibiguity.  The algorithm in PENNY gives up more easily on displaying these
349states.
350<P>
351If the A option is not used, then the program will assume 0 as the
352ancestral state for those characters following the Camin-Sokal method,
353and will assume that the ancestral state is unknown for those characters
354following Wagner parsimony.  If any characters have unknown ancestral
355states, and if the resulting tree is rooted (even by outgroup),
356a table will be printed out
357showing the best guesses of which are the ancestral states in each
358character.  You will find it useful to understand the difference between
359the Camin-Sokal parsimony criterion with unknown ancestral state and the Wagner
360parsimony criterion.
361<P>
362At the beginning of the program are a series of constants,
363which can be changed to help adapt the program to different computer systems. 
364Two are the initial values of howmany and howoften,
365constants "often" and "many".  Constant "maxtrees"
366is the maximum number of tied trees that will be stored.
367<P>
368<HR>
369<P>
370<H3>TEST DATA SET</H3>
371<P>
372<TABLE><TR><TD BGCOLOR=white>
373<PRE>
374    7    6
375Alpha1    110110
376Alpha2    110110
377Beta1     110000
378Beta2     110000
379Gamma1    100110
380Delta     001001
381Epsilon   001110
382</PRE>
383</TD></TR></TABLE>
384<P>
385<HR>
386<P>
387<H3>TEST SET OUTPUT (with all numerical options turned on)</H3>
388<P>
389<TABLE><TR><TD BGCOLOR=white>
390<PRE>
391
392Penny algorithm, version 3.6a3
393 branch-and-bound to find all most parsimonious trees
394
395 7 species,   6 characters
396Wagner parsimony method
397
398
399Name         Characters
400----         ----------
401
402Alpha1       11011 0
403Alpha2       11011 0
404Beta1        11000 0
405Beta2        11000 0
406Gamma1       10011 0
407Delta        00100 1
408Epsilon      00111 0
409
410
411
412requires a total of              8.000
413
414    3 trees in all found
415
416
417
418
419  +-----------------Alpha1   
420  ! 
421  !        +--------Alpha2   
422--1        ! 
423  !  +-----4     +--Epsilon   
424  !  !     !  +--6 
425  !  !     +--5  +--Delta     
426  +--2        ! 
427     !        +-----Gamma1   
428     ! 
429     !           +--Beta2     
430     +-----------3 
431                 +--Beta1     
432
433  remember: this is an unrooted tree!
434
435
436steps in each character:
437         0   1   2   3   4   5   6   7   8   9
438     *-----------------------------------------
439    0!       1   1   1   2   2   1           
440
441From    To     Any Steps?    State at upper node
442                             ( . means same as in the node below it on tree)
443
444          1                11011 0
445  1    Alpha1       no     ..... .
446  1       2         no     ..... .
447  2       4         no     ..... .
448  4    Alpha2       no     ..... .
449  4       5         yes    .0... .
450  5       6         yes    0.1.. .
451  6    Epsilon      no     ..... .
452  6    Delta        yes    ...00 1
453  5    Gamma1       no     ..... .
454  2       3         yes    ...00 .
455  3    Beta2        no     ..... .
456  3    Beta1        no     ..... .
457
458
459
460
461  +-----------------Alpha1   
462  ! 
463--1  +--------------Alpha2   
464  !  ! 
465  !  !           +--Epsilon   
466  +--2        +--6 
467     !  +-----5  +--Delta     
468     !  !     ! 
469     +--4     +-----Gamma1   
470        ! 
471        !        +--Beta2     
472        +--------3 
473                 +--Beta1     
474
475  remember: this is an unrooted tree!
476
477
478steps in each character:
479         0   1   2   3   4   5   6   7   8   9
480     *-----------------------------------------
481    0!       1   1   1   2   2   1           
482
483From    To     Any Steps?    State at upper node
484                             ( . means same as in the node below it on tree)
485
486          1                11011 0
487  1    Alpha1       no     ..... .
488  1       2         no     ..... .
489  2    Alpha2       no     ..... .
490  2       4         no     ..... .
491  4       5         yes    .0... .
492  5       6         yes    0.1.. .
493  6    Epsilon      no     ..... .
494  6    Delta        yes    ...00 1
495  5    Gamma1       no     ..... .
496  4       3         yes    ...00 .
497  3    Beta2        no     ..... .
498  3    Beta1        no     ..... .
499
500
501
502
503  +-----------------Alpha1   
504  ! 
505  !           +-----Alpha2   
506--1  +--------2 
507  !  !        !  +--Beta2     
508  !  !        +--3 
509  +--4           +--Beta1     
510     ! 
511     !           +--Epsilon   
512     !        +--6 
513     +--------5  +--Delta     
514              ! 
515              +-----Gamma1   
516
517  remember: this is an unrooted tree!
518
519
520steps in each character:
521         0   1   2   3   4   5   6   7   8   9
522     *-----------------------------------------
523    0!       1   1   1   2   2   1           
524
525From    To     Any Steps?    State at upper node
526                             ( . means same as in the node below it on tree)
527
528          1                11011 0
529  1    Alpha1       no     ..... .
530  1       4         no     ..... .
531  4       2         no     ..... .
532  2    Alpha2       no     ..... .
533  2       3         yes    ...00 .
534  3    Beta2        no     ..... .
535  3    Beta1        no     ..... .
536  4       5         yes    .0... .
537  5       6         yes    0.1.. .
538  6    Epsilon      no     ..... .
539  6    Delta        yes    ...00 1
540  5    Gamma1       no     ..... .
541
542</PRE>
543</TD></TR></TABLE>
544</BODY>
545</HTML>
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