Толық филогенез және есептеу филогенетикасы

Term used in computational phylogenetics
Perfect phylogeny is a term used in computational phylogenetics to denote a phylogenetic tree in which all internal nodes may be labeled such that all characters evolve down the tree without homoplasy. That is, characteristics do not hold to evolutionary convergence, and do not have analogous structures. Statistically, this can be represented as an ancestor having state "0" in all characteristics where 0 represents a lack of that characteristic. Each of these characteristics changes from 0 to 1 exactly once and never reverts to state 0. It is rare that actual data adheres to the concept of perfect phylogeny.

Perfect phylogeny is a theoretical framework that can also be used in more practical methods. One such example is that of Incomplete Directed Perfect Phylogeny. This concept involves utilizing perfect phylogenies with real, and therefore incomplete and imperfect, datasets. Such a method utilizes SINEs to determine evolutionary similarity. These Short Interspersed Elements are present across many genomes and can be identified by their flanking sequences. SINEs provide information on the inheritance of certain traits across different species. Unfortunately, if a SINE is missing it is difficult to know whether those SINEs were present prior to the deletion. By utilizing algorithms derived from perfect phylogeny data we are able to attempt to reconstruct a phylogenetic tree in spite of these limitations. Perfect phylogeny is also used in the construction of haplotype maps. By utilizing the concepts and algorithms described in perfect phylogeny one can determine information regarding missing and unavailable haplotype data. By assuming that the set of haplotypes that result from genotype mapping corresponds and adheres to the concept of perfect phylogeny (as well as other assumptions such as perfect Mendelian inheritance and the fact that there is only one mutation per SNP), one is able to infer missing haplotype data. Inferring a phylogeny from noisy VAF data under the PPM is a hard problem. For example, tools such as MEDICC, TuMult, and FISHtrees allow the number of copies of a given genetic element, or ploidy, to both increase, or decrease, thus effectively allowing the removal of mutations.