Tree House Explorer: A Novel Genome Browser for Phylogenomics.

Tree House Explorer (THEx) is a genome browser that integrates phylogenomic data and genomic annotations into a single interactive platform for combined analysis. THEx allows users to visualize genome-wide variation in evolutionary histories and genetic divergence on a chromosome-by-chromosome basis, with continuous sliding window comparisons to gene annotations (GFF/GTF), recombination rates, and other user-specified, highly customizable feature annotations. THEx provides a new platform for interactive phylogenomic data visualization to analyze and interpret the diverse evolutionary histories woven throughout genomes.

Fast algorithms for computing phylogenetic divergence time.

Background: The inference of species divergence time is a key step in most phylogenetic studies. Methods have been available for the last ten years to perform the inference, but the performance of the methods does not yet scale well to studies with hundreds of taxa and thousands of DNA base pairs. For example a study of 349 primate taxa was estimated to require over 9 months of processing time.

An efficient and extensible approach for compressing phylogenetic trees.

Background: Biologists require new algorithms to efficiently compress and store their large collections of phylogenetic trees. Our previous work showed that TreeZip is a promising approach for compressing phylogenetic trees. In this paper, we extend our TreeZip algorithm by handling trees with weighted branches.

A new support measure to quantify the impact of local optima in phylogenetic analyses.

Phylogentic analyses are often incorrectly assumed to have stabilized to a single optimum. However, a set of trees from a phylogenetic analysis may contain multiple distinct local optima with each optimum providing different levels of support for each clade. For situations with multiple local optima, we propose p-support which is a clade support measure that shows the impact optima have on a final consensus tree.

Impacts of the Cretaceous Terrestrial Revolution and KPg extinction on mammal diversification.

Previous analyses of relations, divergence times, and diversification patterns among extant mammalian families have relied on supertree methods and local molecular clocks. We constructed a molecular supermatrix for mammalian families and analyzed these data with likelihood-based methods and relaxed molecular clocks. Phylogenetic analyses resulted in a robust phylogeny with better resolution than phylogenies from supertree methods.

Big cat phylogenies, consensus trees, and computational thinking.

Phylogenetics seeks to deduce the pattern of relatedness between organisms by using a phylogeny or evolutionary tree. For a given set of organisms or taxa, there may be many evolutionary trees depicting how these organisms evolved from a common ancestor. As a result, consensus trees are a popular approach for summarizing the shared evolutionary relationships in a group of trees.

Large-scale analysis of phylogenetic search behavior.

Phylogenetic analysis is used in all branches of biology with applications ranging from studies on the origin of human populations to investigations of the transmission patterns of HIV. Most phylogenetic analyses rely on effective heuristics for obtaining accurate trees. However, relatively little work has been done to analyze quantitatively the behavior of phylogenetic heuristics in tree space.

MrsRF: an efficient MapReduce algorithm for analyzing large collections of evolutionary trees.

Background: MapReduce is a parallel framework that has been used effectively to design large-scale parallel applications for large computing clusters. In this paper, we evaluate the viability of the MapReduce framework for designing phylogenetic applications. The problem of interest is generating the all-to-all Robinson-Foulds distance matrix, which has many applications for visualizing and clustering large collections of evolutionary trees.

Using tree diversity to compare phylogenetic heuristics.

Background: Evolutionary trees are family trees that represent the relationships between a group of organisms. Phylogenetic heuristics are used to search stochastically for the best-scoring trees in tree space. Given that better tree scores are believed to be better approximations of the true phylogeny, traditional evaluation techniques have used tree scores to determine the heuristics that find the best scores in the fastest time.

Rec-I-DCM3: a fast algorithmic technique for reconstructing large phylogenetic trees.

Phylogenetic trees are commonly reconstructed based on hard optimization problems such as maximum parsimony (MP) and maximum likelihood (ML). Conventional MP heuristics for producing phylogenetic trees produce good solutions within reasonable time on small datasets (up to a few thousand sequences), while ML heuristics are limited to smaller datasets (up to a few hundred sequences). However, since MP (and presumably ML) is NP-hard, such approaches do not scale when applied to large datasets.