Editing Cladogram (section)

===Cladogram selection===
There are several [[algorithms]] available to identify the "best" cladogram.<ref>
{{cite book|
title=Cladistics: The Theory and Practice of Parsimony Analysis |
last=Kitching | first=Ian|
isbn=978-0-19-850138-1|
year=1998|
publisher=Oxford University Press
}}{{page needed|date=March 2015}}
</ref> Most algorithms use a [[Metric (mathematics)|metric]] to measure how consistent a candidate cladogram is with the data. Most cladogram algorithms use the mathematical techniques of [[Optimization (mathematics)|optimization]] and minimization.

In general, cladogram generation algorithms must be implemented as computer programs, although some algorithms can be performed manually when the data sets are modest (for example, just a few species and a couple of characteristics).

Some algorithms are useful only when the characteristic data are molecular (DNA, RNA); other algorithms are useful only when the characteristic data are morphological. Other algorithms can be used when the characteristic data includes both molecular and morphological data.

Algorithms for cladograms or phylogenetic trees include [[least squares]], [[neighbor-joining]], [[Maximum_parsimony_(phylogenetics)|parsimony]], [[maximum likelihood]], and [[Bayesian inference]].

Biologists sometimes use the term [[Maximum parsimony (phylogenetics)|parsimony]] for a specific kind of cladogram generation algorithm and sometimes as an umbrella term for all phylogenetic algorithms.<ref>{{cite journal |doi=10.1038/361603a0 |pmid=8437621 |title=The powers and pitfalls of parsimony |journal=Nature |volume=361 |issue=6413 |pages=603–7 |year=1993 |last1=Stewart |first1=Caro-Beth |bibcode=1993Natur.361..603S |s2cid=4350103 }}</ref>

Algorithms that perform optimization tasks (such as building cladograms) can be sensitive to the order in which the input data (the list of species and their characteristics) is presented. Inputting the data in various orders can cause the same algorithm to produce different "best" cladograms. In these situations, the user should input the data in various orders and compare the results.

Using different algorithms on a single data set can sometimes yield different "best" cladograms, because each algorithm may have a unique definition of what is "best".

Because of the astronomical number of possible cladograms, algorithms cannot guarantee that the solution is the overall best solution. A nonoptimal cladogram will be selected if the program settles on a local minimum rather than the desired global minimum.<ref>
{{cite book|
last=Foley|
first=Peter|
title=Cladistics: A Practical Course in Systematics|
year=1993|
page=[https://archive.org/details/cladisticspracti0000unse/page/66 66]|
publisher=Oxford Univ. Press|
isbn=978-0-19-857766-9|
url=https://archive.org/details/cladisticspracti0000unse/page/66}}</ref> To help solve this problem, many cladogram algorithms use a [[simulated annealing]] approach to increase the likelihood that the selected cladogram is the optimal one.<ref>{{cite journal |doi=10.1111/j.1096-0031.1999.tb00277.x |title=The Parsimony Ratchet, a New Method for Rapid Parsimony Analysis |journal=Cladistics |volume=15 |issue=4 |pages=407–414 |year=1999 |last1=Nixon |first1=Kevin C. |pmid=34902938 |s2cid=85720264 }}</ref>

The [[Basal (phylogenetics)|basal position]] is the direction of the base (or root) of a rooted phylogenetic tree or cladogram. A basal clade is the earliest clade (of a given taxonomic rank[a]) to branch within a larger clade.