DISTANCE-BASED PHYLOGENETIC ALGORITHMS: NEW INSIGHTS AND APPLICATIONS

被引:5
|
作者
Pompei, S. [1 ,2 ]
Caglioti, E. [3 ]
Loreto, V. [1 ,2 ]
Tria, F. [2 ]
机构
[1] Univ Roma La Sapienza, Dipartimento Fis, I-00185 Rome, Italy
[2] ISI Fdn, I-10133 Turin, Italy
[3] Univ Roma La Sapienza, Dipartimento Matemat, I-00185 Rome, Italy
关键词
Phylogeny; distance-based methods; noise and horizontal transfer; trees; TREE; DYNAMICS;
D O I
10.1142/S0218202510004672
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
Phylogenetic methods have recently been rediscovered in several interesting areas among which immunodynamics, epidemiology and many branches of evolutionary dynamics. In many interesting cases the reconstruction of a correct phylogeny is blurred by high mutation rates and/or horizontal transfer events. As a consequence, a divergence arises between the true evolutionary distances and the distances between pairs of taxa as inferred from the available data, making the phylogenetic reconstruction a challenging problem. Mathematically this divergence translates in the non-additivity of the actual distances between taxa and the quest for new algorithms able to efficiently cope with these effects is wide open. In distance-based reconstruction methods, two properties of additive distances were extensively exploited as antagonist criteria to drive phylogeny reconstruction: on the one hand a local property of quartets, i.e. sets of four taxa in a tree, the four-point condition; on the other hand, a recently proposed formula that allows to write the tree length as a function of the distances between taxa, the Pauplin's formula. A deeper comprehension of the effects of the non-additivity on the inspiring principles of the existing reconstruction algorithms is thus of paramount importance. In this paper we present a comparative analysis of the performances of the most important distance-based phylogenetic algorithms. We focus in particular on the dependence of their performances on two main sources of non-additivity: back-mutation processes and horizontal transfer processes. The comparison is carried out in the framework of a set of generative algorithms for phylogenies that incorporate non-additivity in a tunable way.
引用
收藏
页码:1511 / 1532
页数:22
相关论文
共 50 条
  • [21] Distance-based variable generation with applications to the FACT experiment
    Voigt, Tobias
    Fried, Roland
    Rhode, Wolfgang
    Temme, Fabian
    JOURNAL OF APPLIED STATISTICS, 2016, 43 (07) : 1186 - 1197
  • [22] Distance-based discriminant analysis method and its applications
    Serhiy Kosinov
    Thierry Pun
    Pattern Analysis and Applications, 2008, 11 : 227 - 246
  • [23] Distance-based test feature classifiers and its applications
    Lashkia, V.
    Kaneko, S.
    Aleshin, S.
    IEICE Transactions on Information and Systems, 2000, E83-D (04) : 904 - 913
  • [24] Distance-based discriminant analysis method and its applications
    Kosinov, Serhiy
    Pun, Thierry
    PATTERN ANALYSIS AND APPLICATIONS, 2008, 11 (3-4) : 227 - 246
  • [25] Distance-based test feature classifiers and its applications
    Lashkia, V
    Kaneko, S
    Aleshin, S
    IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS, 2000, E83D (04): : 904 - 913
  • [26] Some New Results on Distance-Based Polynomials
    Behmaram, A.
    Yousefi-Azari, H.
    Ashrafi, A. R.
    MATCH-COMMUNICATIONS IN MATHEMATICAL AND IN COMPUTER CHEMISTRY, 2011, 65 (01) : 39 - 50
  • [27] A Distance-Based Method for Inferring Phylogenetic Networks in the Presence of Incomplete Lineage Sorting
    Yu, Yun
    Nakhleh, Luay
    BIOINFORMATICS RESEARCH AND APPLICATIONS (ISBRA 2015), 2015, 9096 : 378 - 389
  • [28] How to account for reticulation events in phylogenetic analysis: A comparison of distance-based methods
    Lapointe, FJ
    JOURNAL OF CLASSIFICATION, 2000, 17 (02) : 175 - 184
  • [29] Relaxed Neighbor Joining: A Fast Distance-Based Phylogenetic Tree Construction Method
    Jason Evans
    Luke Sheneman
    James Foster
    Journal of Molecular Evolution, 2006, 62 : 785 - 792
  • [30] Minimum reference network for temperature modeling through distance-based algorithms
    Mendoza, Helver Novoa
    Camero, Edwin Martinez
    Granell, Emilio
    Giraldo, Faber Danilo
    2022 XVLIII LATIN AMERICAN COMPUTER CONFERENCE (CLEI 2022), 2022,