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Trips-Viz:一个用于分析公共和用户生成的核糖体图谱数据的环境。

Trips-Viz: an environment for the analysis of public and user-generated ribosome profiling data.

机构信息

School of Biochemistry and Cell Biology, University College Cork, Cork, Ireland.

Ribomaps Ltd, Western Gateway Bld, Western Rd, Cork, Ireland.

出版信息

Nucleic Acids Res. 2021 Jul 2;49(W1):W662-W670. doi: 10.1093/nar/gkab323.

Abstract

Trips-Viz (https://trips.ucc.ie/) is an interactive platform for the analysis and visualization of ribosome profiling (Ribo-Seq) and shotgun RNA sequencing (RNA-seq) data. This includes publicly available and user generated data, hence Trips-Viz can be classified as a database and as a server. As a database it provides access to many processed Ribo-Seq and RNA-seq data aligned to reference transcriptomes which has been expanded considerably since its inception. Here, we focus on the server functionality of Trips-viz which also has been greatly improved. Trips-viz now enables visualisation of proteomics data from a large number of processed mass spectrometry datasets. It can be used to support translation inferred from Ribo-Seq data. Users are now able to upload a custom reference transcriptome as well as data types other than Ribo-Seq/RNA-Seq. Incorporating custom data has been streamlined with RiboGalaxy (https://ribogalaxy.ucc.ie/) integration. The other new functionality is the rapid detection of translated open reading frames (ORFs) through a simple easy to use interface. The analysis of differential expression has been also improved via integration of DESeq2 and Anota2seq in addition to a number of other improvements of existing Trips-viz features.

摘要

Trips-Viz(https://trips.ucc.ie/)是一个用于分析和可视化核糖体分析(Ribo-Seq)和鸟枪法 RNA 测序(RNA-seq)数据的交互平台。它包括公开可用和用户生成的数据,因此 Trips-Viz 可以被归类为数据库和服务器。作为一个数据库,它提供了对许多经过处理的核糖体分析和 RNA-seq 数据的访问,这些数据自成立以来已经大大扩展。在这里,我们关注 Trips-viz 的服务器功能,该功能也得到了极大的改进。Trips-viz 现在可以可视化来自大量经过处理的质谱数据集的蛋白质组学数据。它可以用于支持从 Ribo-Seq 数据推断的翻译。用户现在可以上传自定义参考转录本以及除了 Ribo-Seq/RNA-Seq 之外的其他数据类型。与 RiboGalaxy(https://ribogalaxy.ucc.ie/)集成后,整合自定义数据变得更加简化。另一个新功能是通过简单易用的界面快速检测翻译的开放阅读框(ORFs)。通过整合 DESeq2 和 Anota2seq,以及对现有 Trips-viz 功能的许多其他改进,差异表达的分析也得到了改善。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/81bf/8262740/2cb7f438cbf3/gkab323gra1.jpg

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