RNA-seq data science: From raw data to effective interpretation.
RNA-seq data science: From raw data to effective interpretation.
复制标题
DOI：
10.3389/fgene.2023.997383
复制
发表时间：
2023
影响因子：
3.7
通讯作者：
Mangul, Serghei
中科院分区：
文献类型：
--
作者：
Deshpande, Dhrithi;Chhugani, Karishma;Chang, Yutong;Karlsberg, Aaron;Loeffler, Caitlin;Zhang, Jinyang;Muszynska, Agata;Munteanu, Viorel;Yang, Harry;Rotman, Jeremy;Tao, Laura;Balliu, Brunilda;Tseng, Elizabeth;Eskin, Eleazar;Zhao, Fangqing;Mohammadi, Pejman;Labaj, Pawel P.;Mangul, Serghei
关键词：
RNA测序（RNA-seq）已成为现代生物学和临床科学中的示范性技术。它的巨大受欢迎程度在很大程度上是由于生物信息学社区不断努力开发准确和可扩展的计算工具来分析它产生的大量转录组数据。RNA-seq分析使基因及其相应的转录本能够被探测用于各种目的，例如检测新的外显子或完整转录本，评估基因和替代转录本的表达，以及研究替代剪接结构。然而，从原始RNA-seq数据中获得有意义的生物信号可能是一个挑战，因为数据的巨大规模以及不同测序技术的固有局限性，例如扩增偏倚或文库制备偏倚。克服这些技术挑战的需要推动了新型计算工具的快速发展，这些工具根据技术进步而发展和多样化，导致目前无数的RNA-seq工具。这些工具与生物医学研究人员的各种计算技能相结合，有助于释放RNA-seq的全部潜力。这篇综述的目的是解释RNA-seq数据计算分析中的基本概念，并定义特定学科的术语。
RNA sequencing (RNA-seq) has become an exemplary technology in modern biology and clinical science. Its immense popularity is due in large part to the continuous efforts of the bioinformatics community to develop accurate and scalable computational tools to analyze the enormous amounts of transcriptomic data that it produces. RNA-seq analysis enables genes and their corresponding transcripts to be probed for a variety of purposes, such as detecting novel exons or whole transcripts, assessing expression of genes and alternative transcripts, and studying alternative splicing structure. It can be a challenge, however, to obtain meaningful biological signals from raw RNA-seq data because of the enormous scale of the data as well as the inherent limitations of different sequencing technologies, such as amplification bias or biases of library preparation. The need to overcome these technical challenges has pushed the rapid development of novel computational tools, which have evolved and diversified in accordance with technological advancements, leading to the current myriad of RNA-seq tools. These tools, combined with the diverse computational skill sets of biomedical researchers, help to unlock the full potential of RNA-seq. The purpose of this review is to explain basic concepts in the computational analysis of RNA-seq data and define discipline-specific jargon.
登录
查看更多内容
影响因子：
12.3
作者：
Castel SE;Levy-Moonshine A;Mohammadi P;Banks E;Lappalainen T
通讯作者：
Lappalainen T
全面鉴定环状RNA的内部结构和选择性剪接事件
影响因子：
16.6
作者：
Gao Y;Wang J;Zheng Y;Zhang J;Chen S;Zhao F
通讯作者：
Zhao F
DOI：
10.1093/bioinformatics/btu638
发表时间：
2015-01-15
期刊：
Bioinformatics (Oxford, England)
影响因子：
--
作者：
Anders S;Pyl PT;Huber W
通讯作者：
Huber W
影响因子：
48
作者：
Engstrom, Par G.;Steijger, Tamara;Sipos, Botond;Grant, Gregory R.;Kahles, Andre;Raetsch, Gunnar;Goldman, Nick;Hubbard, Tim J.;Harrow, Jennifer;Guigo, Roderic;Bertone, Paul
通讯作者：
Bertone, Paul
影响因子：
5.8
作者：
Cheng, Jun;Metge, Franziska;Dieterich, Christoph
通讯作者：
Dieterich, Christoph