融合基因
背景(考古学)
计算生物学
计算机科学
DNA测序
融合
传感器融合
基因
生物
人工智能
遗传学
语言学
哲学
古生物学
作者
Erin E. Heyer,James Blackburn
出处
期刊:BioEssays
[Wiley]
日期:2020-04-19
卷期号:42 (7)
被引量:18
标识
DOI:10.1002/bies.202000016
摘要
Abstract Fusion genes formed by chromosomal rearrangements are common drivers of cancer. Recent innovations in the field of next‐generation sequencing (NGS) have seen a dynamic shift from traditional fusion detection approaches, such as visual characterization by fluorescence, to more precise multiplexed methods. There are many different NGS‐based approaches to fusion gene detection and deciding on the most appropriate method can be difficult. Beyond the experimental approach, consideration needs to be given to factors such as the ease of implementation, processing time, associated costs, and the level of expertise required for data analysis. Here, the different NGS‐based methods for fusion gene detection, the basic principles underlying the techniques, and the benefits and limitations of each approach are reviewed. This article concludes with a discussion of how NGS will impact fusion gene detection in a clinical context and from where the next innovations are evolving.
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