非编码 RNA 数据的统计分析。
Statistical analysis of non-coding RNA data.
机构信息
Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA.
Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA.
出版信息
Cancer Lett. 2018 Mar 28;417:161-167. doi: 10.1016/j.canlet.2017.12.029. Epub 2018 Jan 4.
With rapid progress in high-throughput genome technology, the study of noncoding RNA has arisen as a highly popular topic in biomedical research. Noncoding RNA plays fundamental roles in cell proliferation, cell differentiation and epigenetic regulation, and the study of noncoding RNA will yield novel insights into gene regulation and provide new clues for disease treatment. However, due to the large volume and diverse functions of noncoding RNAs, the analysis of these RNAs has proved to be a challenging task. In this review, we review the commonly used computational tools for the identification of noncoding RNAs, and discuss popular statistical tools for their analysis. Due to the large body of noncoding RNA classes, we focus on the analysis of microRNA and long noncoding RNA, two of the most widely studied classes of noncoding RNAs. Specific examples are provided to show the context of the analysis. This review aims to provide up-to-date information on existing tools and methods for identifying and analyzing noncoding RNA.
随着高通量基因组技术的快速发展，非编码 RNA 的研究已成为生物医学研究中一个非常热门的课题。非编码 RNA 在细胞增殖、细胞分化和表观遗传调控中发挥着重要作用，对非编码 RNA 的研究将为基因调控提供新的见解，并为疾病治疗提供新的线索。然而，由于非编码 RNA 的数量庞大且功能多样，对这些 RNA 的分析已被证明是一项具有挑战性的任务。在这篇综述中，我们回顾了常用于识别非编码 RNA 的计算工具，并讨论了用于分析它们的流行统计工具。由于非编码 RNA 种类繁多，我们重点分析了 miRNA 和长非编码 RNA 这两种研究最广泛的非编码 RNA 。提供了具体的例子来说明分析的上下文。本综述旨在提供有关识别和分析非编码 RNA 的现有工具和方法的最新信息。
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