ction什么意思 a python Environment for Tree Explorationcup是什么
Reviewed by Jaime Huerta-Cepas,corresponding author1 Joaquín Dopazo,2 and Toni Gabaldóncorresponding author1
Abstract
floor怎么读
Many bioinformatics analys, ranging from gene clustering to phylogenetics, produce hierarchical trees as their main result. The are ud to reprent the relationships among different biological entities, thus facilitating their analysis and interpretation. A number of standalone programs are available that focus on tree visualization or that perform specific analys on them. However, such applications are rarely suitable for large-scale surveys, in which a higher level of automation is required. Currently, many genome-wide analys rely on tree-like data reprentation and hence there is a growing need for scalable tools to handle tree structures at large scale.
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Keywords: Python, spiking neurons, simulation, integrate and fire, teaching, neural networks, computational neuroscience, software
Background
Here we prent the Environment for Tree Exploration (ETE), a python programming toolkit that assists in the automated manipulation, analysis and visualization of hierarchical trees. ETE libraries provide a broad t of tree handling options as well as specific methods to analyze phylogenetic and clustering trees. Among other features, ETE allows for the independent analysis of tree partitions, has support for the extended newick format, provides an integrated node annotation system and permits to link trees to external data such as multiple quence alignments or numerical arrays. In addition, ETE implements a number of built-in analytical tools, including phylogeny-bad orthology prediction and cluster validation techniques. Finally, ETE's programmable tree drawing engine can be ud to automate the graphical rendering of trees with customized node-specific visualizations.
Conclusions
ETE provides a complete t of methods to manipulate tree data structures that extends
current functionality in other bioinformatic toolkits of a more general purpo. ETE is free software and can be downloaded ics.
Trees are commonly ud to reprent the results of many bioinformatics analys. In particular, such type of binary graphs are ideal to describe the hierarchical relationships among a variety of biological entities. Some common examples are the evolutionary analysis of molecular quences or the clusterization of genes and proteins according to their properties. Besides the information encoded in the topology of trees, branch lengths can also be scaled to provide information on the distances between the different partitions. In phylogenetics, for instance, trees are ud to illustrate the evolutionary relationships among species or molecular quences, considering terminal nodes as extant Operational Taxonomic Units (OTU) and internal nodes as their corresponding ancestors. In such phylogenetic trees, branch lengths are usually proportional to the evolutionary distance among quences. Other applications, such as the analysis of gene expression, u hierarchical clustering analysis to group genes or experimental conditions according to the similarity of their expression patterns. Likewi, trees are u
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d by many protein classification methods and for the analysis of phylogenetic profiles. Thus, the analysis of tree data structures is a common task in many areas of bioinformatics and there is a need for analytical and visualization tools. In this respect, a number of bioinformatic programs do exist that assist in the exploration of hierarchical trees. Most of them, however, consist of standalone applications that are focud on visualization and, occasionally, on performing specific tests. Some well known examples are TreeView [1], a widely ud program for inspecting phylogenetic trees; Cluster Treeview [2], an application for visualizing microarray clustering results; ATV [3], a java program ud to explore phylogenies which provides also some editing options; MEGA [4], an evolutionary genetics analysis suite that includes a built-in tree viewer; and many other recent applications [5-8]. While all the programs are very uful to manage single trees, they can hardly be automatized or adapted to specific needs. Thus, when the analysis of hundreds or thousands of trees is required, the u of standalone programs becomes restrictive, becau a much higher level of automation is required. In such cas, programming toolkits reprent a more adequate framework, since they provide to
look forward tools and methods to handle data at a lower level. Using toolkits, bioinformaticians can easily create their own analysis pipelines and program custom tasks over large collections of data [9]. Several generic bioinformatic toolkits do exist that cover a wide range of programming languages and scopes, with BioPerl [10] and BioPython [11] being the most extensively developed. Together with a broad range of other features, the toolkits allow certain level of interaction with tree data structures. However, only basic actions are currently supported. Alternatively, the PyCogent [12] and P4 bmnh/~pf/p4.html python toolkits can be ud to extend this functionality, although they are mostly focud on phylogenetic reconstruction. R [13], a general purpo statistical framework, does include veral packages to perform statistical tests on clustering and phylogenetic trees. Nevertheless, the packages are focud on performing specific analys rather than in providing tree handling and manipulation features. Finally, in contrast to the great number of standalone tree viewers, programming toolkits offer few, if any, graphical rendering possibilities. An intermediate alternative between standalone viewers and programmatic tree rendering is that of the TreeDyn prog
ram [14], which has support for some scripting options and can be ud to create fully annotated tree images.
In respon to the limitations, we prent here the Environment for Tree Exploration (ETE), a python programming toolkit to analyze, manipulate or visualize any kind of hierarchical tree. It extends the functionality in other toolkits and allows a high level of customization. ETE's drawing features, although less exhaustive than in standalone editors, rely on the Python scripting language, which makes possible to combine advanced tree analys and tree visualization into a single program. The toolkit includes methods to brow and manipulate tree topologies, provides support for the New Hampshire eXtended (NHX) format and allows advanced actions such as node annotation, automatic rooting, cut & paste partitions, tree concatenation, node arch, and branch distance related operations. In addition, ETE implements two specific modules to work with phylogenetic and clustering trees. The phylogenetic extension allows trees to be linked to their corresponding multiple quence alignments, includes two orthology and paralogy prediction algorithms, implements the duplication dating meth
od described in [15] and provides access to the PhylomeDB databa [16]. Similarly, clustering trees can be linked to their source data, which allows tree partitions to be analyzed through veral validation techniques. Additionally, ETE implements a fully programmable drawing engine that can be ud to generate, dynamically, custom tree reprentations in PDF or PNG formats. This drawing engine is fully integrated with the built-in extensions, thus providing pre-defined visualization layouts for clustering trees and phylogenies. A Graphical Ur Interface is also included which allows on the fly interaction with trees.英语转换器
Currently, the ETE toolkit is ud in diver projects, including GEPAS [17], Phylemon [18] and PhylomeDB [15]. ETE package and documentation can be accesd icshazelnut
Implementation
姜澄宇ETE is entirely written in Python [19], a programming language that offers a strong support for integration with other languages and tools, and who popularity is raising am
ong the bioinformatics community [20]. ETE's philosophy is to facilitate the integration with other toolkits as well as to provide a scalable program architecture. Thus, ETE tree objects can be easily imported and expanded by incorporating custom methods and properties. The functionality of the ETE toolkit is divided into veral python modules, which can be imported at convenience. A summary of features of the different modules is shown in Table 酷抠族
