DOLLOP -- Dollo and Polymorphism Parsimony Program
(c) Copyright 1986-1993 by Joseph Felsenstein and by the University of
Washington. Written by Joseph Felsenstein. Permission is granted to copy this
document provided that no fee is charged for it and that this copyright notice
is not removed.
This program carries out the Dollo and polymorphism parsimony methods.
The Dollo parsimony method was first suggested in print in verbal form by Le
Quesne (1974) and was first well-specified by Farris (1977). The method is
named after Louis Dollo since he was one of the first to assert that in
evolution it is harder to gain a complex feature than to lose it. The
algorithm explains the presence of the state 1 by allowing up to one forward
change 0-->1 and as many reversions 1-->0 as are necessary to explain the
pattern of states seen. The program attempts to minimize the number of 1-->0
The assumptions of this method are in effect:
1. We know which state is the ancestral one (state 0).
2. The characters are evolving independently.
3. Different lineages evolve independently.
4. The probability of a forward change (0-->1) is small over the
evolutionary times involved.
5. The probability of a reversion (1-->0) is also small, but still far
larger than the probability of a forward change, so that many reversions are
easier to envisage than even one extra forward change.
6. Retention of polymorphism for both states (0 and 1) is highly
7. The lengths of the segments of the true tree are not so unequal that
two changes in a long segment are as probable as one in a short segment.
One problem can arise when using additive binary recoding to represent a
multistate character as a series of two-state characters. Unlike the Camin-
Sokal, Wagner, and Polymorphism methods, the Dollo method can reconstruct
ancestral states which do not exist. An example is given in my 1979 paper. It
will be necessary to check the output to make sure that this has not occurred.
The polymorphism parsimony method was first used by me, and the results
published (without a clear specification of the method) by Inger (1967). The
method was independently published by Farris (1978a) and by me (1979). The
method assumes that we can explain the pattern of states by no more than one
origination (0-->1) of state 1, followed by retention of polymorphism along as
many segments of the tree as are necessary, followed by loss of state 0 or of
state 1 where necessary. The program tries to minimize the total number of
polymorphic characters, where each polymorphism is counted once for each
segment of the tree in which it is retained.
The assumptions of the polymorphism parsimony method are in effect:
1. The ancestral state (state 0) is known in each character.
2. The characters are evolving independently of each other.
3. Different lineages are evolving independently.
4. Forward change (0-->1) is highly improbable over the length of time
involved in the evolution of the group.
5. Retention of polymorphism is also improbable, but far more probable
that forward change, so that we can more easily envisage much polymorhism than
even one additional forward change.
6. Once state 1 is reached, reoccurrence of state 0 is very improbable,
much less probable than multiple retentions of polymorphism.
7. The lengths of segments in the true tree are not so unequal that we can
more easily envisage retention events occurring in both of two long segments
than one retention in a short segment.
That these are the assumptions of parsimony methods has been documented in
a series of papers of mine: (1973a, 1978b, 1979, 1981b, 1983b, 1988b). For an
opposing view arguing that the parsimony methods make no substantive
assumptions such as these, see the papers by Farris (1983) and Sober (1983a,
1983b), but also read the exchange between Felsenstein and Sober (1986).
The input format is the standard one, with "?", "P", "B" states allowed.
The options are selected using a menu:
Dollo and polymorphism parsimony algorithm, version 3.5c
Settings for this run:
U Search for best tree? Yes
P Parsimony method? Dollo
J Randomize input order of species? No. Use input order
T Use Threshold parsimony? No, use ordinary parsimony
A Use ancestral states in input file? No
M Analyze multiple data sets? No
0 Terminal type (IBM PC, VT52, ANSI)? ANSI
1 Print out the data at start of run No
2 Print indications of progress of run Yes
3 Print out tree Yes
4 Print out steps in each character No
5 Print states at all nodes of tree No
6 Write out trees onto tree file? Yes
Are these settings correct? (type Y or the letter for one to change)
The options U, J, T, A, and M are the usual User Tree, Jumble, Ancestral
States, and Multiple Data Sets options, described either in the main
documentation file or in the Discrete Characters Programs documentation file.
The A (Ancestral States) option allows implementation of the unordered Dollo
parsimony and unordered polymorphism parsimony methods which I have described
elsewhere (1984b). When the A option is used the ancestor is not to be counted
as one of the species. The O (outgroup) option is not available since the tree
produced is already rooted. Since the Dollo and polymorphism methods produce a
rooted tree, the user-defined trees required by the U option have two-way forks
at each level.
The P (Parsimony Method) option is the one that toggles between
polymorphism parsimony and Dollo parsimony. The program defaults to Dollo
The T (Threshold) option has already been described in the Discrete
Characters programs documentation file. Setting T at or below 1.0 but above 0
causes the criterion to become compatibility rather than polymorphism
parsimony, although there is no advantage to using this program instead of MIX
to do a compatibility method. Setting the threshold value higher brings about
an intermediate between the Dollo or polymorphism parsimony methods and the
compatibility method, so that there is some rationale for doing that. Since
the Dollo and polymorphism methods produces a rooted tree, the user-defined
trees required by the U option have two-way forks at each level.
Using a threshold value of 1.0 or lower, but above 0, one can obtain a
rooted (or, if the A option is used with ancestral states of "?", unrooted)
compatibility criterion, but there is no particular advantage to using this
program for that instead of MIX. Higher threshold values are of course
meaningful and provide intermediates between Dollo and compatibility methods.
In the input file the W (Weights) option is available, as usual. It and
the A (Ancestral states) option also require the option to be declared on the
first line of the input file and other information to be present in the input
file. If the Ancestral States information in present in the input file the A
option must be chosen from the menu. The X (Mixed parsimony methods) option is
not available in this program. The F (Factors) option is also not available in
this program, as it would have no effect on the result even if that information
were provided in the input file.
Output is standard: a list of equally parsimonious trees, and, if the user
selects menu option 4, a table of the numbers of reversions or retentions of
polymorphism necessary in each character. If any of the ancestral states has
been specified to be unknown, a table of reconstructed ancestral states is also
provided. When reconstructing the placement of forward changes and reversions
under the Dollo method, keep in mind that each polymorphic state in the input
data will require one "last minute" reversion. This is included in the
tabulated counts. Thus if we have both states 0 and 1 at a tip of the tree the
program will assume that the lineage had state 1 up to the last minute, and
then state 0 arose in that population by reversion, without loss of state 1.
If the user selects menu option 5, a table is printed out after each tree,
showing for each branch whether there are known to be changes in the branch,
and what the states are inferred to have been at the top end of the branch. If
the inferred state is a "?" there may be multiple equally-parsimonious
assignments of states; the user must work these out for themselves by hand.
If the A option is used, then the program will infer, for any character
whose ancestral state is unknown ("?") whether the ancestral state 0 or 1 will
give the best tree. If these are tied, then it may not be possible for the
program to infer the state in the internal nodes, and these will all be printed
as ".". If this has happened and you want to know more about the states at the
internal nodes, you will find helpful to use DOLMOVE to display the tree and
examine its interior states, as the algorithm in DOLMOVE shows all that can be
known in this case about the interior states, including where there is and is
not amibiguity. The algorithm in DOLLOP gives up more easily on displaying
If the U (User Tree) option is used and more than one tree is supplied,
the program also performs a statistical test of each of these trees against the
best tree. This test, which is a version of the test proposed by Alan
Templeton (1983) and evaluated in a test case by me (1985a). It is closely
parallel to a test using log likelihood differences invented by Kishino and
Hasegawa (1989), and uses the mean and variance of step differences between
trees, taken across characters. If the mean is more than 1.96 standard
deviations different then the trees are declared significantly different. The
program prints out a table of the steps for each tree, the differences of each
from the highest one, the variance of that quantity as determined by the step
differences at individual sites, and a conclusion as to whether that tree is or
is not significantly worse than the best one. It is important to understand
that the test assumes that all the binary characters are evolving
independently, which is unlikely to be true for many suites of morphological
The constants at the beginning of the program include maxchr, the maximum
number of characters allowed, "nmlngth", the number of characters in a species
name, and "maxtrees", the maximum number of trees which the program will store
The algorithm is a fairly simple adaptation of the one used in the program
SOKAL, which was formerly in this package and has been superseded by MIX. It
requires two passes through each tree to count the numbers of reversions.
------------------------------TEST DATA SET-----------------------------
---------- TEST SET OUTPUT (with all numerical options on) -------------
Dollo and polymorphism parsimony algorithm, version 3.5c
Dollo parsimony method
Alpha 11011 0
Beta 11000 0
Gamma 10011 0
Delta 00100 1
Epsilon 00111 0
One most parsimonious tree found:
requires a total of 3.000
reversions in each character:
0 1 2 3 4 5 6 7 8 9
0! 0 0 1 1 1 0
From To Any Steps? State at upper node
( . means same as in the node below it on tree)
root 3 yes ..1.. .
3 Delta yes ..... 1
3 4 yes ...11 .
4 Epsilon no ..... .
4 2 yes 1.0.. .
2 Gamma no ..... .
2 1 yes .1... .
1 Beta yes ...00 .
1 Alpha no ..... .