Department of Biomedical Engineering and Genome Center, University of California at Davis, Davis, CA, USA.
Bioinformatics. 2017 Feb 1;33(3):441-443. doi: 10.1093/bioinformatics/btw627.
To serve numerous functional roles, RNA must fold into specific structures. Determining these structures is thus of paramount importance. The recent advent of high-throughput sequencing-based structure profiling experiments has provided important insights into RNA structure and widened the scope of RNA studies. However, as a broad range of approaches continues to emerge, a universal framework is needed to quantitatively ensure consistent and high-quality data. We present SEQualyzer, a visual and interactive application that makes it easy and efficient to gauge data quality, screen for transcripts with high-quality information and identify discordant replicates in structure profiling experiments. Our methods rely on features common to a wide range of protocols and can serve as standards for quality control and analyses.
SEQualyzer is written in R, is platform-independent, and is freely available at http://bme.ucdavis.edu/aviranlab/SEQualyzer.
Supplementary data are available at Bioinformatics online.
为了发挥众多功能,RNA 必须折叠成特定的结构。因此,确定这些结构至关重要。最近,高通量测序的结构分析实验的出现为 RNA 结构提供了重要的见解,并拓宽了 RNA 研究的范围。然而,随着各种方法的不断涌现,需要一个通用的框架来定量保证数据的一致性和高质量。我们提出了 SEQualyzer,这是一个可视化和交互式的应用程序,可轻松高效地评估数据质量,筛选具有高质量信息的转录本,并识别结构分析实验中的不一致重复。我们的方法依赖于广泛协议中常见的特征,可以作为质量控制和分析的标准。
SEQualyzer 是用 R 编写的,与平台无关,可在 http://bme.ucdavis.edu/aviranlab/SEQualyzer 免费获得。
补充数据可在《生物信息学》在线获得。