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RNA-Seq 数据中全基因组差异剪接的软件研究综述。

A survey of software for genome-wide discovery of differential splicing in RNA-Seq data.

机构信息

Department of Cell and Developmental Biology, University of Colorado Anschutz Medical Campus, 12801 17th Ave, rm 12103, MS 8108, PO Box 6511, Aurora, CO 80045, USA.

出版信息

Hum Genomics. 2014 Jan 21;8(1):3. doi: 10.1186/1479-7364-8-3.

Abstract

Alternative splicing is a major contributor to cellular diversity. Therefore the identification and quantification of differentially spliced transcripts in genome-wide transcript analysis is an important consideration. Here, I review the software available for analysis of RNA-Seq data for differential splicing and discuss intrinsic challenges for differential splicing analyses. Three approaches to differential splicing analysis are described, along with their associated software implementations, their strengths, limitations, and caveats. Suggestions for future work include more extensive experimental validation to assess accuracy of the software predictions and consensus formats for outputs that would facilitate visualizations, data exchange, and downstream analyses.

摘要

可变剪接是细胞多样性的主要贡献者。因此,在全基因组转录分析中鉴定和定量差异剪接的转录本是一个重要的考虑因素。在这里,我回顾了用于 RNA-Seq 数据差异剪接分析的软件,并讨论了差异剪接分析的内在挑战。描述了三种差异剪接分析方法,以及它们各自的软件实现、优点、局限性和注意事项。对未来工作的建议包括更广泛的实验验证,以评估软件预测的准确性,以及输出的共识格式,这将有助于可视化、数据交换和下游分析。

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