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TransPi-一个用于从头组装转录组的全面转录组分析管道。

TransPi-a comprehensive TRanscriptome ANalysiS PIpeline for de novo transcriptome assembly.

机构信息

Department of Earth and Environmental Science, Paleontology & Geobiology, Ludwig-Maximilians-Universität München, München, Germany.

Graduate School for Evolution, Ecology and Systematics, Faculty of Biology, Ludwig-Maximilians-Universität München, Planegg-Martinsried, Germany.

出版信息

Mol Ecol Resour. 2022 Jul;22(5):2070-2086. doi: 10.1111/1755-0998.13593. Epub 2022 Feb 18.

Abstract

The use of RNA sequencing (RNA-Seq) data and the generation of de novo transcriptome assemblies have been pivotal for studies in ecology and evolution. This is especially true for nonmodel organisms, where no genome information is available. In such organisms, studies of differential gene expression, DNA enrichment bait design and phylogenetics can all be accomplished with de novo transcriptome assemblies. Multiple tools are available for transcriptome assembly, but no single tool can provide the best assembly for all data sets. Therefore, a multi-assembler approach, followed by a reduction step, is often sought to generate an improved representation of the assembly. To reduce errors in these complex analyses while at the same time attaining reproducibility and scalability, automated workflows have been essential in the analysis of RNA-Seq data. However, most of these tools are designed for species where genome data are used as reference for the assembly process, limiting their use in nonmodel organisms. We present TransPi, a comprehensive pipeline for de novo transcriptome assembly, with minimum user input but without losing the ability of a thorough analysis. A combination of different model organisms, k-mer sets, read lengths and read quantities was used for assessing the tool. Furthermore, a total of 49 nonmodel organisms, spanning different phyla, were also analysed. Compared to approaches using single assemblers only, TransPi produces higher BUSCO completeness percentages, and a concurrent significant reduction in duplication rates. TransPi is easy to configure and can be deployed seamlessly using Conda, Docker and Singularity.

摘要

RNA 测序 (RNA-Seq) 数据的使用和从头转录组组装的生成对于生态学和进化研究至关重要。对于没有基因组信息的非模式生物来说尤其如此。在这些生物中,可以使用从头转录组组装来研究差异基因表达、DNA 富集诱饵设计和系统发育学。有多种工具可用于转录组组装,但没有一种工具可以为所有数据集提供最佳组装。因此,通常会采用多组装器方法,然后进行缩减步骤,以生成组装的改进表示。为了在同时实现可重复性和可扩展性的同时减少这些复杂分析中的错误,自动化工作流程对于 RNA-Seq 数据的分析至关重要。然而,这些工具中的大多数都是为使用基因组数据作为组装过程参考的物种设计的,这限制了它们在非模式生物中的使用。我们提出了 TransPi,这是一种用于从头转录组组装的综合管道,只需最少的用户输入,但不会失去彻底分析的能力。使用不同的模式生物、k-mer 集、读取长度和读取量的组合来评估该工具。此外,还对跨越不同门的总共 49 种非模式生物进行了分析。与仅使用单个组装器的方法相比,TransPi 产生了更高的 BUSCO 完整性百分比,并同时显著降低了重复率。TransPi 易于配置,可以使用 Conda、Docker 和 Singularity 无缝部署。

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