Agalma: an automated phylogenomics workflow.
Agalma: an automated phylogenomics workflow.
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DOI：
10.1186/1471-2105-14-330
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发表时间：
2013-11-19
影响因子：
3
通讯作者：
Zapata F
中科院分区：
文献类型：
--
作者：
Dunn CW;Howison M;Zapata F
在过去的十年中，转录组数据已成为许多系统发育研究的重要组成部分。它们是蛋白质编码基因序列的成本效益来源，并帮助项目从几个基因发展到数百或数千个基因。系统发育研究现在定期包括来自新测序的转录组的基因，以及公开可用的转录组和基因组。然而，实施这样的基因组学研究是计算密集型的，需要协调使用许多复杂的软件工具，并且包括多个步骤，其中没有公开的工具存在。因此，系统基因组学研究一直是手工或半自动化的。除了花费大量的用户时间之外，这使得重复的基因组分析难以再现、比较和扩展。此外，在一项研究中所作的方法改进往往不容易在其他研究中加以应用和评价。我们提出了Agalma，一个自动化的工具，构建矩阵的基因组分析。用户提供原始的Illumina转录组数据，Agalma生成注释的组件，比对的基因序列矩阵，初步的基因组学和详细的诊断，使研究人员能够对中间分析步骤和最终结果进行广泛的评估。来自其他来源的序列，例如外部组装的基因组和转录组，也可以并入分析中。Agalma建立在BioLite生物信息学框架之上，该框架可跟踪来源，分析处理器和内存使用情况，记录诊断，管理元数据，安装依赖关系，记录版本号和调用外部程序，并为分析的所有阶段提供丰富的HTML报告。Agalma包括一个小的测试数据集和这些数据的内置测试分析。除了描述Agalma，我们在这里提出了一个更大的七分类群数据集的样本分析。Agalma可在https://bitbucket.org/caseywdunn/agalma下载。Agalma允许实现复杂的基因组分析，并明确地描述为一系列高级命令。这将使基因组学研究能够容易地复制、修改和扩展。Agalma还通过提供与测试数据捆绑在一起的完整模块化工作流程来促进方法开发，这将允许在完整的基因组分析的背景下进一步优化每个步骤。
In the past decade, transcriptome data have become an important component of many phylogenetic studies. They are a cost-effective source of protein-coding gene sequences, and have helped projects grow from a few genes to hundreds or thousands of genes. Phylogenetic studies now regularly include genes from newly sequenced transcriptomes, as well as publicly available transcriptomes and genomes. Implementing such a phylogenomic study, however, is computationally intensive, requires the coordinated use of many complex software tools, and includes multiple steps for which no published tools exist. Phylogenomic studies have therefore been manual or semiautomated. In addition to taking considerable user time, this makes phylogenomic analyses difficult to reproduce, compare, and extend. In addition, methodological improvements made in the context of one study often cannot be easily applied and evaluated in the context of other studies. We present Agalma, an automated tool that constructs matrices for phylogenomic analyses. The user provides raw Illumina transcriptome data, and Agalma produces annotated assemblies, aligned gene sequence matrices, a preliminary phylogeny, and detailed diagnostics that allow the investigator to make extensive assessments of intermediate analysis steps and the final results. Sequences from other sources, such as externally assembled genomes and transcriptomes, can also be incorporated in the analyses. Agalma is built on the BioLite bioinformatics framework, which tracks provenance, profiles processor and memory use, records diagnostics, manages metadata, installs dependencies, logs version numbers and calls to external programs, and enables rich HTML reports for all stages of the analysis. Agalma includes a small test data set and a built-in test analysis of these data. In addition to describing Agalma, we here present a sample analysis of a larger seven-taxon data set. Agalma is available for download at https://bitbucket.org/caseywdunn/agalma. Agalma allows complex phylogenomic analyses to be implemented and described unambiguously as a series of high-level commands. This will enable phylogenomic studies to be readily reproduced, modified, and extended. Agalma also facilitates methods development by providing a complete modular workflow, bundled with test data, that will allow further optimization of each step in the context of a full phylogenomic analysis.
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影响因子：
3.4
作者：
Roure B;Rodriguez-Ezpeleta N;Philippe H
通讯作者：
Philippe H
影响因子：
48
作者：
Langmead, Ben;Salzberg, Steven L.
通讯作者：
Salzberg, Steven L.
Biopython：用于计算分子生物学和生物信息学的免费 Python 工具。
DOI：
10.1093/bioinformatics/btp163
发表时间：
2009-06-01
期刊：
Bioinformatics (Oxford, England)
影响因子：
--
作者：
Cock PJ;Antao T;Chang JT;Chapman BA;Cox CJ;Dalke A;Friedberg I;Hamelryck T;Kauff F;Wilczynski B;de Hoon MJ
通讯作者：
de Hoon MJ
影响因子：
3.7
作者：
Ranwez V;Harispe S;Delsuc F;Douzery EJ
通讯作者：
Douzery EJ
影响因子：
64.8
作者：
通讯作者：
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