T-REX: reconstructing and visualizing phylogenetic trees and reticulation networks.

T-REX (tree and reticulogram reconstruction) is an application to reconstruct phylogenetic trees and reticulation networks from distance matrices. The application includes a number of tree fitting methods like NJ, UNJ or ADDTREE which have been very popular in phylogenetic analysis. At the same time, the software comprises several new methods of phylogenetic analysis such as: tree reconstruction using weights, tree inference from incomplete distance matrices or modeling a reticulation network for a collection of objects or species. T-REX also allows the user to visualize obtained tree or network structures using Hierarchical, Radial or Axial types of tree drawing and manipulate them interactively. AVAILABILITY: T-REX is a freeware package available online at: http://www.fas.umontreal.ca/biol/casgrain/en/labo/t-rex     

TreeViewJ: An application for viewing and analyzing phylogenetic trees

Background  

Phylogenetic trees are widely used to visualize evolutionary relationships between different organisms or samples of the same organism. There exists a variety of both free and commercial tree visualization software available, but limitations in these programs often require researchers to use multiple programs for analysis, annotation, and the production of publication-ready images.     

MZmine 2: Modular framework for processing,visualizing, and analyzing mass spectrometry-based molecular profile data

Background  

Mass spectrometry (MS) coupled with online separation methods is commonly applied for differential and quantitative profiling of biological samples in metabolomic as well as proteomic research. Such approaches are used for systems biology, functional genomics, and biomarker discovery, among others. An ongoing challenge of these molecular profiling approaches, however, is the development of better data processing methods. Here we introduce a new generation of a popular open-source data processing toolbox, MZmine 2.     

Phylogenetic trees: visualizing, customizing and detecting incongruence

Summary: TreeIllustrator is a user-friendly application to visualizeand customize phylogenetic trees. It has a broad range of functionsand capabilities, such as dragging of nodes, different treeshapes, zooming and searching capabilities, and support forlarge trees. It acts as a solution that integrates the specificityof visualizing phylogenetic trees and the customization optionsof a drawing program. It also contains a simple and effectivemethod that compares a custom tree with the Tree of Life, bydetecting incongruence. Availability: A free version is available online at http://nexus.ugent.be/geert/ Contact: wim.vancriekinge{at}ugent.be     

SplitsTree: analyzing and visualizing evolutionary data

MOTIVATION: Real evolutionary data often contain a number of different and sometimes conflicting phylogenetic signals, and thus do not always clearly support a unique tree. To address this problem, Bandelt and Dress (Adv. Math., 92, 47-05, 1992) developed the method of split decomposition. For ideal data, this method gives rise to a tree, whereas less ideal data are represented by a tree-like network that may indicate evidence for different and conflicting phylogenies. RESULTS: SplitsTree is an interactive program, for analyzing and visualizing evolutionary data, that implements this approach. It also supports a number of distances transformations, the computation of parsimony splits, spectral analysis and bootstrapping.      

BIMLR: A method for constructing rooted phylogenetic networks from rooted phylogenetic trees

Rooted phylogenetic trees constructed from different datasets (e.g. from different genes) are often conflicting with one another, i.e. they cannot be integrated into a single phylogenetic tree. Phylogenetic networks have become an important tool in molecular evolution, and rooted phylogenetic networks are able to represent conflicting rooted phylogenetic trees. Hence, the development of appropriate methods to compute rooted phylogenetic networks from rooted phylogenetic trees has attracted considerable research interest of late. The C_ASS algorithm proposed by van Iersel et al. is able to construct much simpler networks than other available methods, but it is extremely slow, and the networks it constructs are dependent on the order of the input data. Here, we introduce an improved C_ASS algorithm, BIMLR. We show that BIMLR is faster than C_ASS and less dependent on the input data order. Moreover, BIMLR is able to construct much simpler networks than almost all other methods. BIMLR is available at http://nclab.hit.edu.cn/wangjuan/BIMLR/.     

BactMAP: An R package for integrating,analyzing and visualizing bacterial microscopy data

High-throughput analyses of single-cell microscopy data are a critical tool within the field of bacterial cell biology. Several programs have been developed to specifically segment bacterial cells from phase-contrast images. Together with spot and object detection algorithms, these programs offer powerful approaches to quantify observations from microscopy data, ranging from cell-to-cell genealogy to localization and movement of proteins. Most segmentation programs contain specific post-processing and plotting options, but these options vary between programs and possibilities to optimize or alter the outputs are often limited. Therefore, we developed BactMAP (Bacterial toolbox for Microscopy Analysis & Plotting), a command-line based R package that allows researchers to transform cell segmentation and spot detection data generated by different programs into various plots. Furthermore, BactMAP makes it possible to perform custom analyses and change the layout of the output. Because BactMAP works independently of segmentation and detection programs, inputs from different sources can be compared within the same analysis pipeline. BactMAP complies with standard practice in R which enables the use of advanced statistical analysis tools, and its graphic output is compatible with ggplot2, enabling adjustable plot graphics in every operating system. User feedback will be used to create a fully automated Graphical User Interface version of BactMAP in the future. Using BactMAP, we visualize key cell cycle parameters in Bacillus subtilis and Staphylococcus aureus, and demonstrate that the DNA replication forks in Streptococcus pneumoniae dissociate and associate before splitting of the cell, after the Z-ring is formed at the new quarter positions. BactMAP is available from https://veeninglab.com/bactmap .     

A new balance index for phylogenetic trees

Several indices that measure the degree of balance of a rooted phylogenetic tree have been proposed so far in the literature. In this work we define and study a new index of this kind, which we call the total cophenetic index: the sum, over all pairs of different leaves, of the depth of their lowest common ancestor. This index makes sense for arbitrary trees, can be computed in linear time and it has a larger range of values and a greater resolution power than other indices like Colless’ or Sackin’s. We compute its maximum and minimum values for arbitrary and binary trees, as well as exact formulas for its expected value for binary trees under the Yule and the uniform models of evolution. As a byproduct of this study, we obtain an exact formula for the expected value of the Sackin index under the uniform model, a result that seems to be new in the literature.     

A metric for phylogenetic trees based on matching

Comparing two or more phylogenetic trees is a fundamental task in computational biology. The simplest outcome of such a comparison is a pairwise measure of similarity, dissimilarity, or distance. A large number of such measures have been proposed, but so far all suffer from problems varying from computational cost to lack of robustness; many can be shown to behave unexpectedly under certain plausible inputs. For instance, the widely used Robinson-Foulds distance is poorly distributed and thus affords little discrimination, while also lacking robustness in the face of very small changes--reattaching a single leaf elsewhere in a tree of any size can instantly maximize the distance. In this paper, we introduce a new pairwise distance measure, based on matching, for phylogenetic trees. We prove that our measure induces a metric on the space of trees, show how to compute it in low polynomial time, verify through statistical testing that it is robust, and finally note that it does not exhibit unexpected behavior under the same inputs that cause problems with other measures. We also illustrate its usefulness in clustering trees, demonstrating significant improvements in the quality of hierarchical clustering as compared to the same collections of trees clustered using the Robinson-Foulds distance.     

Visualizations for taxonomic and phylogenetic trees

MOTIVATION: Despite substantial efforts to develop and populate the back-ends of biological databases, front-ends to these systems often rely on taxonomic expertise. This research applies techniques from human-computer interaction research to the biodiversity domain. RESULTS: We developed an interactive node-link tool, TaxonTree, illustrating the value of a carefully designed interaction model, animation, and integrated searching and browsing towards retrieval of biological names and other information. Users tested the tool using a new, large integrated dataset of animal names with phylogenetic-based and classification-based tree structures. These techniques also translated well for a tool, DoubleTree, to allow comparison of trees using coupled interaction. Our approaches will be useful not only for biological data but as general portal interfaces.     

Aligning,analyzing, and visualizing sequences for antibody engineering: Automated recognition of immunoglobulin variable region features

The analysis and comparison of large numbers of immunoglobulin (Ig) sequences that arise during an antibody selection campaign can be time‐consuming and tedious. Typically, the identification and annotation of framework as well as complementarity‐determining regions (CDRs) is based on multiple sequence alignments using standardized numbering schemes, which allow identification of equivalent residues among different family members but often necessitate expert knowledge and manual intervention. Moreover, due to the enormous length variability of some CDRs the benefit of conventional Ig numbering schemes is limited and the calculation of correct sequence alignments can become challenging. Whereas, in principle, a well established set of rules permits the assignment of CDRs from the amino acid sequence alone, no currently available sequence alignment editor provides an algorithm to annotate new Ig sequences accordingly. Here we present a unique pattern matching method implemented into our recently developed ANTIC ALIgN editor that automatically identifies all hypervariable and framework regions in experimentally elucidated antibody sequences using so‐called “regular expressions.” By combination of this widely supported software syntax with the unique capabilities of real‐time aligning, editing and analyzing extended sets of amino acid and/or nucleotide sequences simultaneously on a local workstation, ANTIC ALIgN provides a powerful utility for antibody engineering. Proteins 2016; 85:65–71. © 2016 Wiley Periodicals, Inc.     

Biodiversity,Shapley value and phylogenetic trees: some remarks

Journal of Mathematical Biology - This paper explores the main differences between the Shapley values of a set of taxa introduced by Haake et al. (J Math Biol 56:479–497, 2007....     

DrugViz: a Cytoscape plugin for visualizing and analyzing small molecule drugs in biological networks

SUMMARY: DrugViz is a Cytoscape plugin that is designed to visualize and analyze small molecules within the framework of the interactome. DrugViz can import drug-target network information in an extended SIF file format to Cytoscape and display the two-dimensional (2D) structures of small molecule nodes in a unified visualization environment. It also can identify small molecule nodes by means of three different 2D structure searching methods, namely isomorphism, substructure and fingerprint-based similarity searches. After selections, users can furthermore conduct a two-side clustering analysis on drugs and targets, which allows for a detailed analysis of the active compounds in the network, and elucidate relationships between these drugs and targets. DrugViz represents a new tool for the analysis of data from chemogenomics, metabolomics and systems biology. AVAILABILITY: DrugViz and data set used in Application are freely available for download at http://202.127.30.184:8080/software.html.     

Limit theorems for patterns in phylogenetic trees

Studying the shape of phylogenetic trees under different random models is an important issue in evolutionary biology. In this paper, we propose a general framework for deriving detailed statistical results for patterns in phylogenetic trees under the Yule–Harding model and the uniform model, two of the most fundamental random models considered in phylogenetics. Our framework will unify several recent studies which were mainly concerned with the mean value and the variance. Moreover, refined statistical results such as central limit theorems, Berry–Esseen bounds, local limit theorems, etc., are obtainable with our approach as well. A key contribution of the current study is that our results are applicable to the whole range of possible sizes of the pattern.