Maximum parsimony (phylogenetics)

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only a matter of definition). If this is the case, there are four remaining possibilities. A and C can both be +, in which case all taxa are the same and all the trees have the same length. A can be + and C can be -, in which case only one character is different, and we cannot learn anything, as all trees have the same length. Similarly, A can be - and C can be +. The only remaining possibility is that A and C are both -. In this case, however, the evidence suggests that A and C group together, and B and D together. As a consequence, if the "true tree" is a tree of this type, the more data we collect (i.e. the more characters we study), the more the evidence will support the wrong tree. Of course, except in mathematical simulations, we never know what the "true tree" is. Thus, unless we are able to devise a model that is guaranteed to accurately recover the "true tree," any other optimality criterion or weighting scheme could also, in principle, be statistically inconsistent. The bottom line is, that while statistical inconsistency is an interesting theoretical issue, it is empirically a purely metaphysical concern, outside the realm of empirical testing. Any method could be inconsistent, and there is no way to know for certain whether it is, or not. It is for this reason that many systematists characterize their phylogenetic results as hypotheses of relationship.

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complementarily, they do not require passing through intermediate states. Ordered characters have a particular sequence in which the states must occur through evolution, such that going between some states requires passing through an intermediate. This can be thought of complementarily as having different costs to pass between different pairs of states. In the eye-color example above, it is possible to leave it unordered, which imposes the same evolutionary "cost" to go from brown-blue, green-blue, green-hazel, etc. Alternatively, it could be ordered brown-hazel-green-blue; this would normally imply that it would cost two evolutionary events to go from brown-green, three from brown-blue, but only one from brown-hazel. This can also be thought of as requiring eyes to evolve through a "hazel stage" to get from brown to green, and a "green stage" to get from hazel to blue, etc. For many characters, it is not obvious if and how they should be ordered. On the contrary, for characters that represent discretization of an underlying continuous variable, like shape, size, and ratio characters, ordering is logical, and simulations have shown that this improves ability to recover correct clades, while decreasing the recovering of erroneous clades.

346:) add an unpleasant wrinkle to the problem of inferring phylogeny. For a number of reasons, two organisms can possess a trait inferred to have not been present in their last common ancestor: If we naively took the presence of this trait as evidence of a relationship, we would infer an incorrect tree. Empirical phylogenetic data may include substantial homoplasy, with different parts of the data suggesting sometimes very different relationships. Methods used to estimate phylogenetic trees are explicitly intended to resolve the conflict within the data by picking the phylogenetic tree that is the best fit to all the data overall, accepting that some data simply will not fit. It is often mistakenly believed that parsimony assumes that convergence is rare; in fact, even convergently derived characters have some value in maximum-parsimony-based phylogenetic analyses, and the prevalence of convergence does not systematically affect the outcome of parsimony-based methods. 540:

relationships is actually increased. Consider analysis that produces the following tree: (fish, (lizard, (whale, (cat, monkey)))). Adding a rat and a walrus will probably reduce the support for the (whale, (cat, monkey)) clade, because the rat and the walrus may fall within this clade, or outside of the clade, and since these five animals are all relatively closely related, there should be more uncertainty about their relationships. Within error, it may be impossible to determine any of these animals' relationships relative to one another. However, the rat and the walrus will probably add character data that cements the grouping any two of these mammals exclusive of the fish or the lizard; where the initial analysis might have been misled, say, by the presence of fins in the fish and the whale, the presence of the walrus, with blubber and fins like a whale but whiskers like a cat and a rat, firmly ties the whale to the mammals.

658:, as is sometimes claimed) is used as a measure of support. Technically, it is supposed to be a measure of repeatability, the probability that that branch (node, clade) would be recovered if the taxa were sampled again. Experimental tests with viral phylogenies suggest that the bootstrap percentage is not a good estimator of repeatability for phylogenetics, but it is a reasonable estimator of accuracy. In fact, it has been shown that the bootstrap percentage, as an estimator of accuracy, is biased, and that this bias results on average in an underestimate of confidence (such that as little as 70% support might really indicate up to 95% confidence). However, the direction of bias cannot be ascertained in individual cases, so assuming that high values bootstrap support indicate even higher confidence is unwarranted. 675:

not necessarily what it does. Branch support values are often fairly low for modestly-sized data sets (one or two steps being typical), but they often appear to be proportional to bootstrap percentages. As data matrices become larger, branch support values often continue to increase as bootstrap values plateau at 100%. Thus, for large data matrices, branch support values may provide a more informative means to compare support for strongly-supported branches. However, interpretation of decay values is not straightforward, and they seem to be preferred by authors with philosophical objections to the bootstrap (although many morphological systematists, especially paleontologists, report both).

503:(and characters) included in the analysis. Also, because more taxa require more branches to be estimated, more uncertainty may be expected in large analyses. Because data collection costs in time and money often scale directly with the number of taxa included, most analyses include only a fraction of the taxa that could have been sampled. Indeed, some authors have contended that four taxa (the minimum required to produce a meaningful unrooted tree) are all that is necessary for accurate phylogenetic analysis, and that more characters are more valuable than more taxa in phylogenetics. This has led to a raging controversy about taxon sampling. 650:

with different taxa is not straightforward. The bootstrap, resampling with replacement (sample x items randomly out of a sample of size x, but items can be picked multiple times), is only used on characters, because adding duplicate taxa does not change the result of a parsimony analysis. The bootstrap is much more commonly employed in phylogenetics (as elsewhere); both methods involve an arbitrary but large number of repeated iterations involving perturbation of the original data followed by analysis. The resulting MPTs from each analysis are pooled, and the results are usually presented on a 50%

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straightforward when character states are not clearly delineated or when they fail to capture all of the possible variation in a character. How would one score the previously mentioned character for a taxon (or individual) with hazel eyes? Or green? As noted above, character coding is generally based on similarity: Hazel and green eyes might be lumped with blue because they are more similar to that color (being light), and the character could be then recoded as "eye color: light; dark." Alternatively, there can be multi-state characters, such as "eye color: brown; hazel, blue; green."

524:(see below) is particularly pronounced with poor taxon sampling, especially in the four-taxon case. This is a well-understood case in which additional character sampling may not improve the quality of the estimate. As taxa are added, they often break up long branches (especially in the case of fossils), effectively improving the estimation of character state changes along them. Because of the richness of information added by taxon sampling, it is even possible to produce highly accurate estimates of phylogenies with hundreds of taxa using only a few thousand characters. 803:

methods result from the search strategy and consensus method employed, rather than the optimization used. Also, analyses of 38 molecular and 86 morphological empirical datasets have shown that the common mechanism assumed by the evolutionary models used in model-based phylogenetics apply to most molecular, but few morphological datasets. This finding validates the use of model-based phylogenetics for molecular data, but suggests that for morphological data, parsimony remains advantageous, at least until more sophisticated models become available for phenotypic data.

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condition inferred to have been present in ancient ancestors of mammals, whose testicles were internal. This inferred similarity between whales and ancient mammal ancestors is in conflict with the tree we accept based on the weight of other characters, since it implies that the mammals with external testicles should form a group excluding whales. However, among the whales, the reversal to internal testicles actually correctly associates the various types of whales (including dolphins and porpoises) into the group

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but this may result in a relatively large number of such homoplastic events. It would be more appropriate to say that parsimony assumes only the minimum amount of change implied by the data. As above, this does not require that these were the only changes that occurred; it simply does not infer changes for which there is no evidence. The shorthand for describing this, to paraphrase Farris is that "parsimony minimizes assumed homoplasies, it does not assume that homoplasy is minimal."

725:, and occurs, for example, where there are long branches (a high level of substitutions) for two characters (A & C), but short branches for another two (B & D). A and B diverged from a common ancestor, as did C and D. Of course, to know that a method is giving you the wrong answer, you would need to know what the correct answer is. This is generally not the case in science. For this reason, some view statistical consistency as irrelevant to empirical phylogenetic questions. 2592: 842:). One area where parsimony still holds much sway is in the analysis of morphological data, because—until recently—stochastic models of character change were not available for non-molecular data, and they are still not widely implemented. Parsimony has also recently been shown to be more likely to recover the true tree in the face of profound changes in evolutionary ("model") parameters (e.g., the rate of evolutionary change) within a tree. 25: 2269: 782:

be meant if the statement "evolution is parsimonious" were in fact true. This could be taken to mean that more character changes may have occurred historically than are predicted using the parsimony criterion. Because parsimony phylogeny estimation reconstructs the minimum number of changes necessary to explain a tree, this is quite possible. However, it has been shown through simulation studies, testing with known

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similarities that cannot be explained by inheritance and common descent. Minimization of required evolutionary change on the one hand and maximization of observed similarities that can be explained as homology on the other may result in different preferred trees when some observed features are not applicable in some groups that are included in the tree, and the latter can be seen as the more general approach.

615:). Today's general consensus is that having multiple MPTs is a valid analytical result; it simply indicates that there is insufficient data to resolve the tree completely. In many cases, there is substantial common structure in the MPTs, and differences are slight and involve uncertainty in the placement of a few taxa. There are a number of methods for summarizing the relationships within this set, including 2604: 253:. Of course, any phylogenetic algorithm could also be statistically inconsistent if the model it employs to estimate the preferred tree does not accurately match the way that evolution occurred in that clade. This is unknowable. Therefore, while statistical consistency is an interesting theoretical property, it lies outside the realm of testability, and is irrelevant to empirical phylogenetic studies. 374:, into which the variations observed are classified. Character states are often formulated as descriptors, describing the condition of the character substrate. For example, the character "eye color" might have the states "blue" and "brown." Characters can have two or more states (they can have only one, but these characters lend nothing to a maximum parsimony analysis, and are often excluded). 127: 911:

Sgaramella-Zonta's conjectures (proven true 22 years later by Rzhetsky and Nei) stating that if the evolutionary distances from taxa were unbiased estimates of the true evolutionary distances then the true phylogeny of taxa would have a length shorter than any other alternative phylogeny compatible with those distances. Rzhetsky and Nei's results set the ME criterion free from the

692: 317:) to directly follow the branching pattern of evolution. Thus we could say that if two organisms possess a shared character, they should be more closely related to each other than to a third organism that lacks this character (provided that character was not present in the last common ancestor of all three, in which case it would be a 795:, described above) may potentially bias results. In both cases, however, there is no way to tell if the result is going to be biased, or the degree to which it will be biased, based on the estimate itself. With parsimony too, there is no way to tell that the data are positively misleading, without comparison to other evidence. 573:

more than one step. Contrary to popular belief, the algorithm does not explicitly assign particular character states to nodes (branch junctions) on a tree: the fewest steps can involve multiple, equally costly assignments and distributions of evolutionary transitions. What is optimized is the total number of changes.

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lowest final project cost. This is because, in the absence of other data, we would assume that all of the relevant contractors have the same risk of cost overruns. In practice, of course, unscrupulous business practices may bias this result; in phylogenetics, too, some particular phylogenetic problems (for example,

305:; the tree with the most favorable score is taken as the best hypothesis of the phylogenetic relationships of the included taxa. Maximum parsimony is used with most kinds of phylogenetic data; until recently, it was the only widely used character-based tree estimation method used for morphological data. 787:

tree. As long as the changes that have not been accounted for are randomly distributed over the tree (a reasonable null expectation), the result should not be biased. In practice, the technique is robust: maximum parsimony exhibits minimal bias as a result of choosing the tree with the fewest changes.

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An analogy can be drawn with choosing among contractors based on their initial (nonbinding) estimate of the cost of a job. The actual finished cost is very likely to be higher than the estimate. Despite this, choosing the contractor who furnished the lowest estimate should theoretically result in the

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procedures, have been employed with parsimony analysis. The jackknife, which involves resampling without replacement ("leave-one-out") can be employed on characters or taxa; interpretation may become complicated in the latter case, because the variable of interest is the tree, and comparison of trees

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Numerous theoretical and simulation studies have demonstrated that highly homoplastic characters, characters and taxa with abundant missing data, and "wildcard" taxa contribute to the analysis. Although excluding characters or taxa may appear to improve resolution, the resulting tree is based on less

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Parsimony is often characterized as implicitly adopting the position that evolutionary change is rare, or that homoplasy (convergence and reversal) is minimal in evolution. This is not entirely true: parsimony minimizes the number of convergences and reversals that are assumed by the preferred tree,

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It is often stated that parsimony is not relevant to phylogenetic inference because "evolution is not parsimonious." In most cases, there is no explicit alternative proposed; if no alternative is available, any statistical method is preferable to none at all. Additionally, it is not clear what would

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Trees are scored (evaluated) by using a simple algorithm to determine how many "steps" (evolutionary transitions) are required to explain the distribution of each character. A step is, in essence, a change from one character state to another, although with ordered characters some transitions require

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Some systematists prefer to exclude characters known to be, or suspected to be, highly homoplastic or that have a large number of unknown entries ("?"). As noted below, theoretical and simulation work has demonstrated that this is likely to sacrifice accuracy rather than improve it. This is also the

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It is also possible to apply differential weighting to individual characters. This is usually done relative to a "cost" of 1. Thus, some characters might be seen as more likely to reflect the true evolutionary relationships among taxa, and thus they might be weighted at a value 2 or more; changes in

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Assume for simplicity that we are considering a single binary character (it can either be + or -). Because the distance from B to D is small, in the vast majority of all cases, B and D will be the same. Here, we will assume that they are both + (+ and - are assigned arbitrarily and swapping them is

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contain a particular clade (node, branch). It can be thought of as the number of steps you have to add to lose that clade; implicitly, it is meant to suggest how great the error in the estimate of the score of the MPT must be for the clade to no longer be supported by the analysis, although this is

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Characters can be treated as unordered or ordered. For a binary (two-state) character, this makes little difference. For a multi-state character, unordered characters can be thought of as having an equal "cost" (in terms of number of "evolutionary events") to change from any one state to any other;

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viral phylogenies, and congruence with other methods, that the accuracy of parsimony is in most cases not compromised by this. Parsimony analysis uses the number of character changes on trees to choose the best tree, but it does not require that exactly that many changes, and no more, produced the

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of any sort. This has often been levelled as a criticism, since there is certainly error in estimating the most-parsimonious tree, and the method does not inherently include any means of establishing how sensitive its conclusions are to this error. Several methods have been used to assess support.

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A maximum parsimony analysis runs in a very straightforward fashion. Trees are scored according to the degree to which they imply a parsimonious distribution of the character data. The most parsimonious tree for the dataset represents the preferred hypothesis of relationships among the taxa in the

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data; it has been empirically determined that certain base changes (A-C, A-T, G-C, G-T, and the reverse changes) occur much less often than others (A-G, C-T, and their reverse changes). These changes are therefore often weighted more. As shown above in the discussion of character ordering, ordered

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data) are used to distinguish cases where a character cannot be scored from a case where the state is simply unknown. Current implementations of maximum parsimony generally treat unknown values in the same manner: the reasons the data are unknown have no particular effect on analysis. Effectively,

325:, which elephants lack. However, we cannot say that bats and monkeys are more closely related to one another than they are to whales, though the two have external testicles absent in whales, because we believe that the males in the last common ancestral species of the three had external testicles. 261:

In phylogenetics, parsimony is mostly interpreted as favoring the trees that minimize the amount of evolutionary change required (see for example ). Alternatively, phylogenetic parsimony can be characterized as favoring the trees that maximize explanatory power by minimizing the number of observed

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which is a parameter of a given data set, rather than an estimate based on pseudoreplicated subsamples, as are the bootstrap and jackknife procedures described above. Bremer support (also known as branch support) is simply the difference in number of steps between the score of the MPT(s), and the

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Parsimony analysis often returns a number of equally most-parsimonious trees (MPTs). A large number of MPTs is often seen as an analytical failure, and is widely believed to be related to the number of missing entries ("?") in the dataset, characters showing too much homoplasy, or the presence of

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A subtle difference distinguishes the maximum-parsimony criterion from the ME criterion: while maximum-parsimony is based on an abductive heuristic, i.e., the plausibility of the simplest evolutionary hypothesis of taxa with respect to the more complex ones, the ME criterion is based on Kidd and

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employed; an incorrect model can produce a biased result - just like parsimony. In addition, they are still quite computationally slow relative to parsimony methods, sometimes requiring weeks to run large datasets. Most of these methods have particularly avid proponents and detractors; parsimony

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than can be searched exhaustively for more than eight taxa or so. A number of algorithms are therefore used to search among the possible trees. Many of these involve taking an initial tree (usually the favored tree from the last iteration of the algorithm), and perturbing it to see if the change

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Some systematists prefer to exclude taxa based on the number of unknown character entries ("?") they exhibit, or because they tend to "jump around" the tree in analyses (i.e., they are "wildcards"). As noted below, theoretical and simulation work has demonstrated that this is likely to sacrifice

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Data that do not fit a tree perfectly are not simply "noise", they can contain relevant phylogenetic signal in some parts of a tree, even if they conflict with the tree overall. In the whale example given above, the lack of external testicles in whales is homoplastic: It reflects a return to the

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Recent simulation studies suggest that parsimony may be less accurate than trees built using Bayesian approaches for morphological data, potentially due to overprecision, although this has been disputed. Studies using novel simulation methods have demonstrated that differences between inference

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The input data used in a maximum parsimony analysis is in the form of "characters" for a range of taxa. There is no generally agreed-upon definition of a phylogenetic character, but operationally a character can be thought of as an attribute, an axis along which taxa are observed to vary. These

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The trees resulting from parsimony search are unrooted: They show all the possible relationships of the included taxa, but they lack any statement on relative times of divergence. A particular branch is chosen to root the tree by the user. This branch is then taken to be outside all the other

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percentages or decay indices, see below). The cause of this is clear: as additional taxa are added to a tree, they subdivide the branches to which they attach, and thus dilute the information that supports that branch. While support for individual branches is reduced, support for the overall

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Coding characters for phylogenetic analysis is not an exact science, and there are numerous complicating issues. Typically, taxa are scored with the same state if they are more similar to one another in that particular attribute than each is to taxa scored with a different state. This is not

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Inferring phylogenies is not a trivial problem. A huge number of possible phylogenetic trees exist for any reasonably sized set of taxa; for example, a mere ten species gives over two million possible unrooted trees. These possibilities must be searched to find a tree that best fits the data

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Ambiguities in character state delineation and scoring can be a major source of confusion, dispute, and error in phylogenetic analysis using character data. Note that, in the above example, "eyes: present; absent" is also a possible character, which creates issues because "eye color" is not

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Because the most-parsimonious tree is always the shortest possible tree, this means that—in comparison to a hypothetical "true" tree that actually describes the unknown evolutionary history of the organisms under study—the "best" tree according to the maximum-parsimony criterion will often

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Although many studies have been performed, there is still much work to be done on taxon sampling strategies. Because of advances in computer performance, and the reduced cost and increased automation of molecular sequencing, sample sizes overall are on the rise, and studies addressing the

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topologically labile "wildcard" taxa (which may have many missing entries). Numerous methods have been proposed to reduce the number of MPTs, including removing characters or taxa with large amounts of missing data before analysis, removing or downweighting highly homoplastic characters (

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these characters would then count as two evolutionary "steps" rather than one when calculating tree scores (see below). There has been much discussion in the past about character weighting. Most authorities now weight all characters equally, although exceptions are common. For example,

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of character states. These character states can not only determine where that taxon is placed on the tree, they can inform the entire analysis, possibly causing different relationships among the remaining taxa to be favored by changing estimates of the pattern of character changes.

445:, or evolutionary transition among the states (for example, "legs: short; medium; long"). Some accept only some of these criteria. Some run an unordered analysis, and order characters that show a clear order of transition in the resulting tree (which practice might be accused of 825:. Each offers potential advantages and disadvantages. In practice, these methods tend to favor trees that are very similar to the most parsimonious tree(s) for the same dataset; however, they allow for complex modelling of evolutionary processes, and as classes of methods are 777:

be related at all, are nonsensical). This is emphatically not the case: as with any form of character-based phylogeny estimation, parsimony is used to test the homologous nature of similarities by finding the phylogenetic tree which best accounts for all of the similarities.

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underestimate the actual evolutionary change that could have occurred. In addition, maximum parsimony is not statistically consistent. That is, it is not guaranteed to produce the true tree with high probability, given sufficient data. As demonstrated in 1978 by

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Empirical, theoretical, and simulation studies have led to a number of dramatic demonstrations of the importance of adequate taxon sampling. Most of these can be summarized by a simple observation: a phylogenetic data matrix has dimensions of characters

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taxa. Doubling the number of taxa doubles the amount of information in a matrix just as surely as doubling the number of characters. Each taxon represents a new sample for every character, but, more importantly, it (usually) represents a new

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assays. Today, distance-based methods are often frowned upon because phylogenetically-informative data can be lost when converting characters to distances. There are a number of distance-matrix methods and optimality criteria, of which the

769:, is that maximum parsimony assumes that the only way two species can share the same nucleotide at the same position is if they are genetically related. This asserts that phylogenetic applications of parsimony assume that all similarity is 457:

data is sometimes pooled in bins and scored as an ordered character. In these cases, the character itself is often downweighted so that small changes in allele frequencies count less than major changes in other characters. Also, the third

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seek to identify supported relationships (in the form of "n-taxon statements," such as the four-taxon statement "(fish, (lizard, (cat, whale)))") rather than whole trees. If the goal of an analysis is a resolved tree, as is the case for

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problem. The only currently available, efficient way of obtaining a solution, given an arbitrarily large set of taxa, is by using heuristic methods which do not guarantee that the shortest tree will be recovered. These methods employ

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accuracy rather than improve it. Although these taxa may generate more most-parsimonious trees (see below), methods such as agreement subtrees and reduced consensus can still extract information on the relationships of interest.

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relationships of hundreds of taxa (or other terminal entities, such as genes) are becoming common. Of course, this is not to say that adding characters is not also useful; the number of characters is increasing as well.

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that minimizes the total number of character-state changes (or minimizes the cost of differentially weighted character-state changes). Under the maximum-parsimony criterion, the optimal tree will minimize the amount of

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according to the optimality criterion. However, the data themselves do not lead to a simple, arithmetic solution to the problem. Ideally, we would expect the distribution of whatever evolutionary characters (such as

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Puttick, Mark N.; O'Reilly, Joseph E.; Tanner, Alastair R.; Fleming, James F.; Clark, James; Holloway, Lucy; Lozano-Fernandez, Jesus; Parry, Luke A.; Tarver, James E.; Pisani, Davide; Donoghue, Philip C. J. (2017).

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is particularly labile, and is sometimes downweighted, or given a weight of 0, on the assumption that it is more likely to exhibit homoplasy. In some cases, repeated analyses are run, with characters reweighted in

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case with characters that are variable in the terminal taxa: theoretical, congruence, and simulation studies have all demonstrated that such polymorphic characters contain significant phylogenetic information.

1184:"Parsimony analysis of unaligned sequence data: maximization of homology and minimization of homoplasy, not Minimization of operationally defined total cost or minimization of equally weighted transformations" 363:

attributes can be physical (morphological), molecular, genetic, physiological, or behavioral. The only widespread agreement on characters seems to be that variation used for character analysis should reflect

213:). In other words, under this criterion, the shortest possible tree that explains the data is considered best. Some of the basic ideas behind maximum parsimony were presented by James S. Farris in 1970 and 228:

the most-parsimonious tree. Instead, the most-parsimonious tree must be sought in "tree space" (i.e., amongst all possible trees). For a small number of taxa (i.e., fewer than nine) it is possible to do an

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Genetic data are particularly amenable to character-based phylogenetic methods such as maximum parsimony because protein and nucleotide sequences are naturally discrete: A particular position in a

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methods fail to produce a definitive assignment for a particular sequence position. Sequence gaps are sometimes treated as characters, although there is no consensus on how they should be coded.

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group. This imparts a sense of relative time to the tree. Incorrect choice of a root can result in incorrect relationships on the tree, even if the tree is itself correct in its unrooted form.

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Goloboff, Pablo A.; Pittman, Michael; Pol, Diego; Xu, Xing (2019). "Morphological data sets fit a common mechanism much more poorly than DNA sequences and call into question the Mkv model".

560:, these methods cannot solve the problem. However, if the tree estimate is so poorly supported, the results of any analysis derived from the tree will probably be too suspect to use anyway. 699:. If branches A & C have a high number of substitutions in the "true tree" (assumed, never actually known except in simulations), then parsimony might interpret parallel changes as 269:). Namely, the supposition of a simpler, more parsimonious chain of events is preferable to the supposition of a more complicated, less parsimonious chain of events. Hence, parsimony ( 387:

the program treats a ? as if it held the state that would involve the fewest extra steps in the tree (see below), although this is not an explicit step in the algorithm.

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Goloboff, Pablo; De Laet, Jan; Ríos-Tamayo, Duniesky; Szumik, Claudia (2021). "A reconsideration of inapplicable characters, and an approximation with step-matrix recoding".

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to progressively approach the best tree. However, it has been shown that there can be "tree islands" of suboptimal solutions, and the analysis can become trapped in these

620: 354:. Still, the determination of the best-fitting tree—and thus which data do not fit the tree—is a complex process. Maximum parsimony is one method developed to do this. 612: 441:

There is a lively debate on the utility and appropriateness of character ordering, but no consensus. Some authorities order characters when there is a clear logical,

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under certain circumstances. Consistency, here meaning the monotonic convergence on the correct answer with the addition of more data, is a desirable property of

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Maximum parsimony is an epistemologically straightforward approach that makes few mechanistic assumptions, and is popular for this reason. However, it may not be

676: 552: 594: 472: 321:). We would predict that bats and monkeys are more closely related to each other than either is to an elephant, because male bats and monkeys possess external 449:). Some authorities refuse to order characters at all, suggesting that it biases an analysis to require evolutionary transitions to follow a particular path. 654:

tree, with individual branches (or nodes) labelled with the percentage of bootstrap MPTs in which they appear. This "bootstrap percentage" (which is not a

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O'Reilly, Joseph E.; Puttick, Mark N.; Parry, Luke; Tanner, Alastair R.; Tarver, James E.; Fleming, James; Pisani, Davide; Donoghue, Philip C. J. (2016).

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While evolution is not an inherently parsimonious process, centuries of scientific experience lend support to the aforementioned principle of parsimony (

2150:"Theoretical foundation of the balanced minimum evolution method of phylogenetic inference and its relationship to weighted least-squares tree fitting" 42: 745:. Thus, complex, flexible heuristics are required to ensure that tree space has been adequately explored. Several heuristics are available, including 616: 876:) or by applying a model of evolution. Notably, distance methods also allow use of data that may not be easily converted to character data, such as 872:. For phylogenetic character data, raw distance values can be calculated by simply counting the number of pairwise differences in character states ( 1576:"Missing data, clade support and "reticulation": the molecular systematics of Heliconius and related genera (Lepidoptera: Nymphalidae) re-examined" 662: 145: 732:

Another complication with maximum parsimony, and other optimality-criterion based phylogenetic methods, is that finding the shortest tree is an

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Kolaczkowski B, Thornton JW (October 2004). "Performance of maximum parsimony and likelihood phylogenetics when evolution is heterogeneous".

666: 367:. Whether it must be directly heritable, or whether indirect inheritance (e.g., learned behaviors) is acceptable, is not entirely resolved. 61: 382:

applicable if eyes are not present. For such situations, a "?" ("unknown") is scored, although sometimes "X" or "-" (the latter usually in

233:, in which every possible tree is scored, and the best one is selected. For nine to twenty taxa, it will generally be preferable to use 1753:"Bayesian methods outperform parsimony but at the expense of precision in the estimation of phylogeny from discrete morphological data" 719:, maximum parsimony can be inconsistent under certain conditions. The category of situations in which this is known to occur is called 68: 907:(ME), that shares with maximum-parsimony the aspect of searching for the phylogeny that has the shortest total sum of branch lengths. 468: 2207: 75: 1375:"Phylogenetic inference using discrete characters: performance of ordered and unordered parsimony and of three-item statements" 1281: 1166: 57: 2635: 2402: 220:

Maximum parsimony is an intuitive and simple criterion, and it is popular for this reason. However, although it is easy to

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data, and is therefore a less reliable estimate of the phylogeny (unless the characters or taxa are non informative, see

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Estimating phylogenies from molecular data, in Mathematical approaches to polymer sequence analysis and related problems

833:. Note, however, that the performance of likelihood and Bayesian methods are dependent on the quality of the particular 627:

takes this one step further, by showing all subtrees (and therefore all relationships) supported by the input trees.

163: 108: 2442: 2447: 2380: 1457:"Impact of errors on cladistic inference: simulation-based comparison between parsimony and three-taxon analysis" 822: 1812:"Weighted parsimony outperforms other methods of phylogenetic inference under models appropriate for morphology" 2608: 2457: 2387: 2129:

Rzhetsky A, Nei M (1993). "Theoretical foundations of the minimum evolution method of phylogenetic inference".

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of a single species. These methods operate by evaluating candidate phylogenetic trees according to an explicit

46: 82: 1416:"Experimental systematics: sensitivity of cladistic methods to polarization and character ordering schemes" 746: 638: 623:, which show common structure by temporarily pruning "wildcard" taxa from every tree until they all agree. 499:

The time required for a parsimony analysis (or any phylogenetic analysis) is proportional to the number of

141: 1694:"Uncertain-tree: discriminating among competing approaches to the phylogenetic analysis of phenotype data" 1496:

Bremer K (July 1988). "The limits of amino acid sequence data in angiosperm phylogenetic reconstruction".

987:

Fitch WM (1971). "Toward defining the course of evolution: minimum change for a specified tree topology".

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that evaluates the decay index for all possible subtree relationships (n-taxon statements) within a tree.

630:

Even if multiple MPTs are returned, parsimony analysis still basically produces a point-estimate, lacking

224:

a phylogenetic tree (by counting the number of character-state changes), there is no algorithm to quickly

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Garwood, Russell J; Knight, Christopher G; Sutton, Mark D; Sansom, Robert S; Keating, Joseph N (2020).

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De Laet J (2005). "Parsimony and the problem of inapplicables in sequence data.". In Albert VA (ed.).

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There are several other methods for inferring phylogenies based on discrete character data, including

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Optimality criterion in which the shortest possible tree that explains the data is considered best

2437: 2235: 1099:

Farris JS (1983). "The logical basis of phylogenetic analysis.". In Platnick NI, Funk VA (eds.).

738: 708: 646: 35: 1656:

Day WH (1987). "Computational complexity of inferring phylogenies from dissimilarity matrices".

273:) is typically sought in inferring phylogenetic trees, and in scientific explanation generally. 2630: 2596: 2320: 2193: 830: 792: 721: 696: 521: 250: 1158: 2572: 2250: 877: 337: 1150: 1028:(1978). "Cases in which parsimony and compatibility methods will be positively misleading". 2409: 2315: 2037: 826: 329: 302: 282: 202: 189: 8: 2452: 2334: 631: 483: 463: 419: 391: 371: 2041: 1310: 535:

It has been observed that inclusion of more taxa tends to lower overall support values (

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or a sequence gap. Thus, character scoring is rarely ambiguous, except in cases where

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of discrete phylogenetic characters and character states to infer one or more optimal

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Parsimony is part of a class of character-based tree estimation methods which use a

237:, which is also guaranteed to return the best tree. For greater numbers of taxa, a 2392: 2346: 2161: 2115: 2103: 2065: 2045: 1992: 1937: 1900: 1882: 1833: 1823: 1782: 1764: 1723: 1705: 1665: 1628: 1587: 1548: 1505: 1468: 1427: 1386: 1337: 1306: 1238: 1195: 1123: 1068: 1037: 996: 958: 929: 924: 912: 454: 423: 266: 238: 234: 2094:

Catanzaro D (2009). "The minimum evolution problem: Overview and classification".

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especially has been advocated as philosophically superior (most notably by ardent

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Character state changes can also be weighted individually. This is often done for

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Grand, Anaïs; Corvez, Adèle; Duque Velez, Lina Maria; Laurin, Michel (2001).

1351: 962: 177: 2166: 2149: 1941: 1871:"Morphological Phylogenetics Evaluated Using Novel Evolutionary Simulations" 1103:. Vol. 2. New York, New York: Columbia University Press. pp. 7–36. 2567: 2513: 2508: 2503: 2488: 2296: 2291: 2175: 2057: 2006: 1957: 1914: 1855: 1796: 1769: 1737: 1710: 1642: 1601: 1517: 1359: 1326:"Character Analysis in Morphological Phylogenetics: Problems and Solutions" 1250: 1207: 1082: 766: 742: 586: 1677: 249:, maximum parsimony can be inconsistent under certain conditions, such as 2562: 2255: 686: 442: 427: 2049: 1414:

Rineau, Valentin; Grand, Anaïs; Zaragüeta, René; Laurin, Michel (2015).

2240: 1838: 1669: 1008: 970: 773:(other interpretations, such as the assertion that two organisms might 712: 471:

to the degree of homoplasy discovered in the previous analysis (termed

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data using a matrix of pairwise distances and reconciled to produce a

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characters can be thought of as a form of character state weighting.

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principle and confer it a solid theoretical and quantitative basis.

24: 853: 839: 783: 399: 383: 364: 322: 1297:

Sober E (1983). "Parsimony in Systematics: Philosophical Issues".

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Goloboff, Pablo A.; Torres, Ambrosio; Arias, J. Salvador (2018).

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Bremer KR (September 1994). "Branch support and tree stability".

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Farris JS (March 1970). "Methods for computing Wagner trees".

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Farris JS (October 2008). "Parsimony and explanatory power".

903:, there exists a phylogenetic estimation criterion, known as 691: 459: 1372: 520:

The most disturbing weakness of parsimony analysis, that of

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Rineau, Valentin; Zaragüeta, René; Laurin, Michel (2018).

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It has been asserted that a major problem, especially for

619:, which show common relationships among all the taxa, and 1868: 885:

criterion is most closely related to maximum parsimony.

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Proceedings of the Royal Society B: Biological Sciences

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can come from a number of different sources, including

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Problems with maximum parsimony phylogenetic inference

475:); this is another technique that might be considered 1498:

Evolution; International Journal of Organic Evolution

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may be too technical for most readers to understand

49:. Unsourced material may be challenged and removed. 1803: 1222: 848:can also be used to generate phylogenetic trees. 2622: 1921: 670:score of the most parsimonious tree that does 2201: 2147: 1276:. Cambridge, UK: Cambridge University Press. 1020: 1018: 1978: 1489: 1094: 1092: 852:distance methods were originally applied to 585:branches of the tree, which together form a 2128: 1862: 1649: 1024: 2208: 2194: 1614: 1574:Brower AV, Garzón-Orduña IJ (April 2018). 1175: 1142: 1015: 2165: 2093: 2078: 1996: 1904: 1886: 1837: 1827: 1786: 1768: 1727: 1709: 1632: 1591: 1472: 1431: 1390: 1379:Biological Journal of the Linnean Society 1341: 1107: 1089: 1072: 942: 164:Learn how and when to remove this message 148:, without removing the technical details. 109:Learn how and when to remove this message 1448: 1407: 1299:Annual Review of Ecology and Systematics 1274:Probability theory: the logic of science 690: 370:Each character is divided into discrete 257:Alternate characterization and rationale 1366: 1317: 1272:Jaynes ET (2003). Bretthorst GL (ed.). 1181: 1148: 982: 980: 2623: 1538: 1495: 1271: 1113: 1098: 1054: 948: 661:Another means of assessing support is 58:"Maximum parsimony" phylogenetics 2189: 1323: 1296: 1265: 986: 146:make it understandable to non-experts 2603: 1157:. Oxford University Press. pp. 977: 888: 120: 47:adding citations to reliable sources 18: 1655: 1311:10.1146/annurev.es.14.110183.002003 13: 2148:Desper R, Gascuel O (March 2004). 1553:10.1111/j.1096-0031.1994.tb00179.x 1510:10.1111/j.1558-5646.1988.tb02497.x 597:) or removing wildcard taxa (the 14: 2647: 2215: 1153:Parsimony, phylogeny and genomics 703:and group A and C together. 494: 357: 2602: 2591: 2590: 2443:Phylogenetic comparative methods 2267: 1998:10.1111/j.1096-0031.2010.00342.x 1658:Bulletin of Mathematical Biology 1128:10.1111/j.1096-0031.2008.00214.x 125: 23: 2448:Phylogenetic niche conservatism 2154:Molecular Biology and Evolution 2141: 2131:Molecular Biology and Evolution 2122: 2087: 2072: 2021: 1972: 1608: 1567: 1532: 1290: 806: 607:and then reanalyzing the data. 34:needs additional citations for 1048: 1: 935: 868:, morphometric analysis, and 715:. As demonstrated in 1978 by 576:There are many more possible 1979:Rindal E, Brower AV (2011). 760: 747:nearest neighbor interchange 276: 7: 2636:Computational phylogenetics 2368:Phylogenetic reconciliation 2275:Evolutionary biology portal 2231:Computational phylogenetics 2079:Catanzaro, Daniele (2010). 1615:Brower AVZ (October 2018). 918: 829:and are not susceptible to 813:Computational phylogenetics 751:tree bisection reconnection 563: 543:To cope with this problem, 297:or reproductively isolated 182:computational phylogenetics 10: 2652: 1343:10.1080/106351501753328811 1055:Brower AV (October 2018). 892: 810: 679:is a decay counterpart to 328:However, the phenomena of 2586: 2558:Phylogenetic nomenclature 2550: 2524: 2476: 2418: 2355: 2284: 2262: 2223: 1474:10.1163/18759866-08701003 1433:10.1163/18759866-08402003 621:pruned agreement subtrees 581:produces a higher score. 558:comparative phylogenetics 426:will be one of the basic 1461:Contributions to Zoology 1420:Contributions to Zoology 827:statistically consistent 739:hill-climbing algorithms 709:statistically consistent 613:safe taxonomic reduction 2438:Molecular phylogenetics 2388:Distance-matrix methods 2236:Molecular phylogenetics 1324:Wiens, John J. (2001). 1042:10.1093/sysbio/27.4.401 652:Majority Rule Consensus 2458:Phylogenetics software 2372:Probabilistic methods 2321:Long branch attraction 1888:10.1093/sysbio/syaa012 1770:10.1098/rsbl.2016.0081 1711:10.1098/rspb.2016.2290 1101:Advances in Cladistics 963:10.1093/sysbio/19.1.83 866:immunological distance 831:long-branch attraction 793:long branch attraction 722:long branch attraction 704: 697:long branch attraction 647:statistical resampling 522:long-branch attraction 338:evolutionary reversals 251:long-branch attraction 211:evolutionary reversals 2251:Evolutionary taxonomy 2167:10.1093/molbev/msh049 2083:. Springer, New York. 1942:10.1093/sysbio/syy077 878:DNA-DNA hybridization 694: 677:Double-decay analysis 553:double-decay analysis 462:position in a coding 340:(collectively termed 2410:Three-taxon analysis 2316:Phylogenetic network 632:confidence intervals 595:successive weighting 473:successive weighting 330:convergent evolution 303:optimality criterion 293:, commonly a set of 203:convergent evolution 190:optimality criterion 43:improve this article 2453:Phylogenetic signal 2050:10.1038/nature02917 2042:2004Natur.431..980K 713:statistical methods 484:nucleotide sequence 464:nucleotide sequence 392:nucleotide sequence 365:heritable variation 241:must be performed. 2381:Bayesian inference 2376:Maximum likelihood 1930:Systematic Biology 1875:Systematic Biology 1704:(1846): 20162290. 1670:10.1007/BF02458863 1330:Systematic Biology 1182:De Laet J (2014). 1030:Systematic Zoology 989:Systematic Zoology 951:Systematic Biology 874:Manhattan distance 835:model of evolution 823:Bayesian inference 819:maximum likelihood 705: 599:phylogenetic trunk 578:phylogenetic trees 545:agreement subtrees 477:circular reasoning 469:inverse proportion 447:circular reasoning 334:parallel evolution 287:phylogenetic trees 207:parallel evolution 2618: 2617: 2363:Maximum parsimony 2356:Inference methods 2304:Phylogenetic tree 2108:10.1002/net.20280 1829:10.1111/cla.12205 1634:10.1111/cla.12216 1593:10.1111/cla.12198 1392:10.1111/bij.12159 1283:978-0-521-59271-0 1243:10.1111/cla.12456 1200:10.1111/cla.12098 1168:978-0-19-856493-5 1074:10.1111/cla.12216 905:Minimum Evolution 895:Minimum Evolution 889:Minimum Evolution 883:minimum evolution 870:genetic distances 846:Distance matrices 755:parsimony ratchet 681:reduced consensus 625:Reduced consensus 549:reduced consensus 311:phenotypic traits 231:exhaustive search 194:phylogenetic tree 186:maximum parsimony 174: 173: 166: 119: 118: 111: 93: 2643: 2606: 2605: 2594: 2593: 2393:Neighbor-joining 2347:Ghost population 2277: 2272: 2271: 2210: 2203: 2196: 2187: 2186: 2180: 2179: 2169: 2145: 2139: 2138: 2126: 2120: 2119: 2091: 2085: 2084: 2076: 2070: 2069: 2025: 2019: 2018: 2000: 1976: 1970: 1969: 1925: 1919: 1918: 1908: 1890: 1866: 1860: 1859: 1841: 1831: 1807: 1801: 1800: 1790: 1772: 1748: 1742: 1741: 1731: 1713: 1688: 1682: 1681: 1653: 1647: 1646: 1636: 1612: 1606: 1605: 1595: 1571: 1565: 1564: 1536: 1530: 1529: 1493: 1487: 1486: 1476: 1452: 1446: 1445: 1435: 1411: 1405: 1404: 1394: 1370: 1364: 1363: 1345: 1321: 1315: 1314: 1294: 1288: 1287: 1269: 1263: 1262: 1226: 1220: 1219: 1179: 1173: 1172: 1156: 1146: 1140: 1139: 1111: 1105: 1104: 1096: 1087: 1086: 1076: 1052: 1046: 1045: 1022: 1013: 1012: 984: 975: 974: 946: 925:Informative site 901:distance methods 455:allele frequency 424:protein sequence 372:character states 239:heuristic search 235:branch-and-bound 192:under which the 169: 162: 158: 155: 149: 129: 128: 121: 114: 107: 103: 100: 94: 92: 51: 27: 19: 2651: 2650: 2646: 2645: 2644: 2642: 2641: 2640: 2621: 2620: 2619: 2614: 2582: 2546: 2520: 2494:Symplesiomorphy 2472: 2414: 2351: 2280: 2273: 2266: 2260: 2224:Relevant fields 2219: 2214: 2184: 2183: 2146: 2142: 2127: 2123: 2092: 2088: 2077: 2073: 2036:(7011): 980–4. 2026: 2022: 1977: 1973: 1926: 1922: 1867: 1863: 1808: 1804: 1763:(4): 20160081. 1757:Biology Letters 1749: 1745: 1689: 1685: 1654: 1650: 1613: 1609: 1572: 1568: 1537: 1533: 1494: 1490: 1453: 1449: 1412: 1408: 1371: 1367: 1322: 1318: 1295: 1291: 1284: 1270: 1266: 1227: 1223: 1180: 1176: 1169: 1147: 1143: 1112: 1108: 1097: 1090: 1053: 1049: 1023: 1016: 1001:10.2307/2412116 985: 978: 947: 943: 938: 921: 899:From among the 897: 891: 862:distance matrix 815: 809: 763: 753:(TBR), and the 717:Joe Felsenstein 689: 617:consensus trees 566: 497: 360: 319:symplesiomorphy 279: 259: 247:Joe Felsenstein 215:Walter M. Fitch 170: 159: 153: 150: 142:help improve it 139: 130: 126: 115: 104: 98: 95: 52: 50: 40: 28: 17: 12: 11: 5: 2649: 2639: 2638: 2633: 2616: 2615: 2613: 2612: 2600: 2587: 2584: 2583: 2581: 2580: 2575: 2570: 2565: 2560: 2554: 2552: 2548: 2547: 2545: 2544: 2539: 2534: 2528: 2526: 2522: 2521: 2519: 2518: 2517: 2516: 2511: 2506: 2498: 2497: 2496: 2491: 2480: 2478: 2474: 2473: 2471: 2470: 2468:Phylogeography 2465: 2460: 2455: 2450: 2445: 2440: 2435: 2430: 2422: 2420: 2419:Current topics 2416: 2415: 2413: 2412: 2407: 2406: 2405: 2400: 2395: 2385: 2384: 2383: 2378: 2370: 2365: 2359: 2357: 2353: 2352: 2350: 2349: 2344: 2343: 2342: 2332: 2323: 2318: 2313: 2312: 2311: 2301: 2300: 2299: 2288: 2286: 2285:Basic concepts 2282: 2281: 2279: 2278: 2263: 2261: 2259: 2258: 2253: 2248: 2243: 2238: 2233: 2227: 2225: 2221: 2220: 2213: 2212: 2205: 2198: 2190: 2182: 2181: 2140: 2121: 2102:(2): 112–125. 2086: 2071: 2020: 1971: 1936:(3): 494–504. 1920: 1881:(5): 897–912. 1861: 1822:(4): 407–437. 1802: 1743: 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2486: 2485: 2482: 2481: 2479: 2475: 2469: 2466: 2464: 2463:Phylogenomics 2461: 2459: 2456: 2454: 2451: 2449: 2446: 2444: 2441: 2439: 2436: 2434: 2433:DNA barcoding 2431: 2429: 2428: 2424: 2423: 2421: 2417: 2411: 2408: 2404: 2403:Least squares 2401: 2399: 2396: 2394: 2391: 2390: 2389: 2386: 2382: 2379: 2377: 2374: 2373: 2371: 2369: 2366: 2364: 2361: 2360: 2358: 2354: 2348: 2345: 2341: 2340:Ghost lineage 2338: 2337: 2336: 2333: 2331: 2327: 2324: 2322: 2319: 2317: 2314: 2310: 2307: 2306: 2305: 2302: 2298: 2295: 2294: 2293: 2290: 2289: 2287: 2283: 2276: 2270: 2265: 2257: 2254: 2252: 2249: 2247: 2244: 2242: 2239: 2237: 2234: 2232: 2229: 2228: 2226: 2222: 2218: 2217:Phylogenetics 2211: 2206: 2204: 2199: 2197: 2192: 2191: 2188: 2177: 2173: 2168: 2163: 2160:(3): 587–98. 2159: 2155: 2151: 2144: 2137:: 21073–1095. 2136: 2132: 2125: 2117: 2113: 2109: 2105: 2101: 2097: 2090: 2082: 2075: 2067: 2063: 2059: 2055: 2051: 2047: 2043: 2039: 2035: 2031: 2024: 2016: 2012: 2008: 2004: 1999: 1994: 1990: 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421: 417: 413: 409: 405: 401: 397: 393: 388: 385: 379: 375: 373: 368: 366: 355: 353: 347: 345: 344: 339: 335: 331: 326: 324: 320: 316: 312: 306: 304: 300: 296: 292: 289:for a set of 288: 284: 274: 272: 268: 267:Occam's razor 263: 254: 252: 248: 242: 240: 236: 232: 227: 223: 218: 216: 212: 208: 204: 200: 195: 191: 187: 183: 179: 178:phylogenetics 168: 165: 157: 147: 143: 137: 134:This article 132: 123: 122: 113: 110: 102: 91: 88: 84: 81: 77: 74: 70: 67: 63: 60: – 59: 55: 54:Find sources: 48: 44: 38: 37: 32:This article 30: 26: 21: 20: 2607: 2595: 2568:Sister group 2551:Nomenclature 2514:Autapomorphy 2509:Synapomorphy 2489:Plesiomorphy 2477:Group traits 2425: 2362: 2297:Cladogenesis 2292:Phylogenesis 2157: 2153: 2143: 2134: 2130: 2124: 2099: 2095: 2089: 2080: 2074: 2033: 2029: 2023: 1991:(3): 331–4. 1988: 1984: 1974: 1933: 1929: 1923: 1878: 1874: 1864: 1819: 1815: 1805: 1760: 1756: 1746: 1701: 1697: 1686: 1664:(4): 461–7. 1661: 1657: 1651: 1624: 1620: 1610: 1583: 1579: 1569: 1544: 1540: 1534: 1501: 1497: 1491: 1467:(1): 25–40. 1464: 1460: 1450: 1423: 1419: 1409: 1382: 1378: 1368: 1333: 1329: 1319: 1302: 1298: 1292: 1273: 1267: 1234: 1230: 1224: 1191: 1187: 1177: 1152: 1144: 1119: 1115: 1109: 1100: 1067:(5): 562–7. 1064: 1060: 1050: 1033: 1029: 992: 988: 957:(1): 83–92. 954: 950: 944: 909: 898: 882: 844: 816: 807:Alternatives 801: 797: 789: 780: 774: 767:paleontology 764: 743:local optima 731: 727: 720: 706: 671: 660: 637: 629: 609: 604:a posteriori 602: 591: 587:monophyletic 583: 575: 571: 567: 542: 534: 530: 526: 519: 513: 508: 505: 498: 489: 481: 451: 440: 436: 416:sequence gap 389: 380: 376: 369: 361: 348: 341: 327: 307: 280: 270: 264: 260: 243: 225: 221: 219: 185: 175: 160: 151: 135: 105: 96: 86: 79: 72: 65: 53: 41:Please help 36:verification 33: 2563:Crown group 2525:Group types 2256:Systematics 1839:11336/57822 1305:: 335–357. 667:decay index 639:Jackknifing 514:combination 443:ontogenetic 428:amino acids 299:populations 2625:Categories 2241:Cladistics 1985:Cladistics 1816:Cladistics 1621:Cladistics 1580:Cladistics 1541:Cladistics 1231:Cladistics 1188:Cladistics 1116:Cladistics 1061:Cladistics 936:References 771:homologous 569:analysis. 432:sequencing 271:sensu lato 69:newspapers 2578:Supertree 2542:Polyphyly 2537:Paraphyly 2532:Monophyly 2504:Apomorphy 2484:Primitive 2427:PhyloCode 2309:Cladogram 1950:1076-836X 1897:1063-5157 1848:0748-3007 1779:1744-9561 1720:0962-8452 1483:1875-9866 1442:1875-9866 1401:0024-4066 1352:1076-836X 1259:234846773 1216:221582410 761:Criticism 665:, or the 537:bootstrap 343:homoplasy 323:testicles 277:In detail 217:in 1971. 199:homoplasy 99:July 2015 2597:Category 2500:Derived 2246:Taxonomy 2176:14694080 2096:Networks 2058:15496922 2015:84907350 2007:34875779 1966:53567539 1958:30445627 1915:32073641 1856:34649370 1797:27095266 1738:28077778 1643:34649374 1602:34645081 1561:84987781 1526:13647124 1518:28563878 1360:12116939 1251:34570932 1208:34772278 1136:32931349 1083:34649374 919:See also 854:phenetic 840:cladists 784:in vitro 601:method) 564:Analysis 400:cytosine 384:sequence 226:generate 154:May 2021 2609:Commons 2335:Lineage 2116:6018514 2066:4385277 2038:Bibcode 1906:7440746 1788:4881353 1729:5247500 1678:3664032 1009:2412116 971:2412028 749:(NNI), 734:NP-hard 656:P-value 422:) in a 420:residue 414:, or a 408:thymine 404:guanine 396:adenine 352:Cetacea 315:alleles 295:species 201:(i.e., 140:Please 83:scholar 2174: 2114: 2064: 2056: 2030:Nature 2013: 2005: 1964: 1956: 1948: 1913: 1903: 1895: 1854: 1846: 1795: 1785: 1777: 1736: 1726: 1718: 1676: 1641: 1600: 1559: 1524: 1516: 1481: 1440: 1399: 1358: 1350: 1280: 1257: 1249: 1214: 1206: 1165: 1161:–116. 1134: 1081: 1007: 969: 860:. The 551:, and 412:uracil 336:, and 283:matrix 209:, and 188:is an 85: 78: 71: 64: 56: 2573:Basal 2398:UPGMA 2330:Grade 2326:Clade 2112:S2CID 2062:S2CID 2011:S2CID 1962:S2CID 1557:S2CID 1522:S2CID 1255:S2CID 1212:S2CID 1132:S2CID 1005:JSTOR 967:JSTOR 509:times 460:codon 406:, or 222:score 90:JSTOR 76:books 2172:PMID 2054:PMID 2003:PMID 1954:PMID 1946:ISSN 1911:PMID 1893:ISSN 1852:PMID 1844:ISSN 1793:PMID 1775:ISSN 1734:PMID 1716:ISSN 1674:PMID 1639:PMID 1598:PMID 1514:PMID 1479:ISSN 1438:ISSN 1397:ISSN 1356:PMID 1348:ISSN 1278:ISBN 1247:PMID 1204:PMID 1163:ISBN 1079:PMID 858:tree 821:and 641:and 501:taxa 291:taxa 180:and 62:news 2328:vs 2162:doi 2104:doi 2046:doi 2034:431 1993:doi 1938:doi 1901:PMC 1883:doi 1834:hdl 1824:doi 1783:PMC 1765:doi 1724:PMC 1706:doi 1702:284 1666:doi 1629:doi 1588:doi 1549:doi 1506:doi 1469:doi 1428:doi 1387:doi 1383:110 1338:doi 1307:doi 1239:doi 1196:doi 1124:doi 1069:doi 1038:doi 997:doi 959:doi 775:not 672:not 313:or 176:In 144:to 45:by 2627:: 2170:. 2158:21 2156:. 2152:. 2135:10 2133:. 2110:. 2100:53 2098:. 2060:. 2052:. 2044:. 2032:. 2009:. 2001:. 1989:27 1987:. 1983:. 1960:. 1952:. 1944:. 1934:68 1932:. 1909:. 1899:. 1891:. 1879:69 1877:. 1873:. 1850:. 1842:. 1832:. 1820:34 1818:. 1814:. 1791:. 1781:. 1773:. 1761:12 1759:. 1755:. 1732:. 1722:. 1714:. 1700:. 1696:. 1672:. 1662:49 1660:. 1637:. 1625:34 1623:. 1619:. 1596:. 1584:34 1582:. 1578:. 1555:. 1545:10 1543:. 1520:. 1512:. 1502:42 1500:. 1477:. 1465:87 1463:. 1459:. 1436:. 1424:84 1422:. 1418:. 1395:. 1381:. 1377:. 1354:. 1346:. 1334:50 1332:. 1328:. 1303:14 1301:. 1253:. 1245:. 1235:37 1233:. 1210:. 1202:. 1192:31 1190:. 1186:. 1159:81 1130:. 1120:24 1118:. 1091:^ 1077:. 1065:34 1063:. 1059:. 1034:27 1032:. 1017:^ 1003:. 993:20 991:. 979:^ 965:. 955:19 953:. 757:. 547:, 479:. 410:/ 402:, 398:, 332:, 205:, 184:, 2209:e 2202:t 2195:v 2178:. 2164:: 2118:. 2106:: 2068:. 2048:: 2040:: 2017:. 1995:: 1968:. 1940:: 1917:. 1885:: 1858:. 1836:: 1826:: 1799:. 1767:: 1740:. 1708:: 1680:. 1668:: 1645:. 1631:: 1604:. 1590:: 1563:. 1551:: 1528:. 1508:: 1485:. 1471:: 1444:. 1430:: 1403:. 1389:: 1362:. 1340:: 1313:. 1309:: 1286:. 1261:. 1241:: 1218:. 1198:: 1171:. 1138:. 1126:: 1085:. 1071:: 1044:. 1040:: 1011:. 999:: 973:. 961:: 167:) 161:( 156:) 152:( 138:. 112:) 106:( 101:) 97:( 87:· 80:· 73:· 66:· 39:.

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Maximum parsimony (phylogenetics)

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