Quartet consistency count method for reconstructing phylogenetic trees

Among the distance based algorithms in phylogenetic tree reconstruction, the neighbor-joining algorithm has been a widely used and effective method. We propose a new algorithm which counts the number of consistent quartets for cherry picking with tie breaking. We show that the success rate of the new algorithm is almost equal to that of neighbor-joining. This gives an explanation of the qualitative nature of neighbor-joining and that of dissimilarity maps from DNA sequence data. Moreover, the new algorithm always reconstructs correct trees from quartet consistent dissimilarity maps.Comment: 11 pages, 5 figure

A fast algorithm for the multiple genome rearrangement problem with weighted reversals and transpositions

<p>Abstract</p> <p>Background</p> <p>Due to recent progress in genome sequencing, more and more data for phylogenetic reconstruction based on rearrangement distances between genomes become available. However, this phylogenetic reconstruction is a very challenging task. For the most simple distance measures (the breakpoint distance and the reversal distance), the problem is NP-hard even if one considers only three genomes.</p> <p>Results</p> <p>In this paper, we present a new heuristic algorithm that directly constructs a phylogenetic tree w.r.t. the weighted reversal and transposition distance. Experimental results on previously published datasets show that constructing phylogenetic trees in this way results in better trees than constructing the trees w.r.t. the reversal distance, and recalculating the weight of the trees with the weighted reversal and transposition distance. An implementation of the algorithm can be obtained from the authors.</p> <p>Conclusion</p> <p>The possibility of creating phylogenetic trees directly w.r.t. the weighted reversal and transposition distance results in biologically more realistic scenarios. Our algorithm can solve today's most challenging biological datasets in a reasonable amount of time.</p

Homology Assessment in Molecular Phylogenetics : Evaluation, Improvement, and Influence of Data Quality on Tree Reconstruction

Considering the final goal of every phylogenetic analysis, the reconstruction of taxon relationships from underlying data, little attention has been paid to the role of alignment accuracy and its impact on tree reconstruction. Alignment masking approaches are methods which detect and remove erroneously aligned sections before tree reconstruction. I describe the effect of two masking methods on alignment quality and tree reconstruction. While masking methods are commonly efficient in detecting ambiguously aligned sequence blocks, all methods more or less lack the ability to detect heterogeneous sequence divergence within sequence alignments. This is a main disadvantage of masking approaches, because undetected heterogeneous sequence divergence can result in a strong bias in tree reconstructions. I give a detailed description of a new developed algorithm and the possibility of tagging branches as an indirect estimation of reliability of a subset of possible splits guided by a topology. The performance of the new algorithm was tested on simulated and empirical data. Considering the tree reconstruction process, the first task is the choice of an appropriate tree reconstruction method. Examining theoretical studies and comparative tests Maximum Likelihood turns out as the first choice for phylogenetic tree reconstructions. I show that the success of Maximum Likelihood depends not only on the degree of alignment quality, but also on the relation of branch length differences of underlying topologies. I tested the robustness of Maximum Likelihood towards different classes of long branch effects in multiple taxon topologies by using simulated fixed data sets under two different 11-taxon trees and a broad range of different branch length conditions with sequence alignments of different length. Some of the most important scripts and pipelines which have been written for the accomplishment of this thesis are also described

Representation in stochastic search for phylogenetictree reconstruction

Phylogenetic tree reconstruction is a process in which the ancestral relationships among a group of organisms are inferred from their DNA sequences. For all but trivial sized data sets, finding the optimal tree is computationally intractable. Many heuristic algorithms exist, but the branch-swapping algorithm used in the software package PAUP is the most popular. This method performs a stochastic search over the space of trees, using a branch-swapping operation to construct neighboring trees in the search space. This study introduces a new stochastic search algorithm that operates over an alternative representation of trees, namely as permutations of taxa giving the order in which they are processed during stepwise addition. Experiments on several data sets suggest that this algorithm for generating an initial tree, when followed by branch-swapping, can produce better trees for a given total amount of time.Engineering and Applied Science

Alignment-free phylogenetic reconstruction: Sample complexity via a branching process analysis

We present an efficient phylogenetic reconstruction algorithm allowing insertions and deletions which provably achieves a sequence-length requirement (or sample complexity) growing polynomially in the number of taxa. Our algorithm is distance-based, that is, it relies on pairwise sequence comparisons. More importantly, our approach largely bypasses the difficult problem of multiple sequence alignment.Comment: Published in at http://dx.doi.org/10.1214/12-AAP852 the Annals of Applied Probability (http://www.imstat.org/aap/) by the Institute of Mathematical Statistics (http://www.imstat.org