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Transcriptome Ortholog Alignment Sequence Tools (TOAST) for phylogenomic dataset assembly

机译:用于系统介月组织组件的转录组正式对准序列工具(吐司)

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Advances in next-generation sequencing technologies have reduced the cost of whole transcriptome analyses, allowing characterization of non-model species at unprecedented levels. The rapid pace of transcriptomic sequencing has driven the public accumulation of a wealth of data for phylogenomic analyses, however lack of tools aimed towards phylogeneticists to efficiently identify orthologous sequences currently hinders effective harnessing of this resource. We introduce TOAST, an open source R software package that can utilize the ortholog searches based on the software Benchmarking Universal Single-Copy Orthologs (BUSCO) to assemble multiple sequence alignments of orthologous loci from transcriptomes for any group of organisms. By streamlining search, query, and alignment, TOAST automates the generation of locus and concatenated alignments, and also presents a series of outputs from which users can not only explore missing data patterns across their alignments, but also reassemble alignments based on user-defined acceptable missing data levels for a given research question. TOAST provides a comprehensive set of tools for assembly of sequence alignments of orthologs for comparative transcriptomic and phylogenomic studies. This software empowers easy assembly of public and novel sequences for any target database of candidate orthologs, and fills a critically needed niche for tools that enable quantification and testing of the impact of missing data. As open-source software, TOAST is fully customizable for integration into existing or novel custom informatic pipelines for phylogenomic inference. Software, a detailed manual, and example data files are available through github carolinafishes.github.io.
机译:下一代测序技术的进步降低了整个转录组分析的成本,允许在前所未有的水平下表征非模型物种。转录组测序的快速速度推动了大量数据积累的系统核发生物分析,然而缺乏针对系统发育者的工具,以有效地识别目前阻碍了这种资源的有效利用这种资源的序列。我们介绍吐司,这是一种可以利用基于软件基准的Ortholog搜索的开源R软件包,该软件基准网上标记通用单拷贝正轨(Busco)来组装来自转录组的多个序列比对从转录组中的任何组织。通过简化搜索,查询和对齐,Toast自动化轨迹和连接对齐的生成,并提出了一系列来自哪些用户,用户不仅可以探索其对齐缺失的数据模式,还可以根据用户定义可接受重新组装对齐缺少给定研究问题的数据级别。 Toast提供了一套全面的工具,用于组装序列变量的序列变量,用于比较转录组和文学组织研究。该软件能够轻松地组装候选地原木的任何目标数据库的公共和新序列,并填补一个批判性的利基,用于使能量化和测试缺失数据的影响的工具。作为开源软件,吐司完全可定制,以集成到现有或新颖的定制信息管制中,用于系统染色的推理。软件,详细的手册和示例数据文件可通过Github CarolinaFishes.github.io获得。

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