| Literature DB >> 28172632 |
Krishna Choudhary1, Luyao Ruan1, Fei Deng1, Nathan Shih1, Sharon Aviran1.
Abstract
Summary: 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. Availability and Implementation: SEQualyzer is written in R, is platform-independent, and is freely available at http://bme.ucdavis.edu/aviranlab/SEQualyzer. Contact: saviran@ucdavis.edu Supplementary Informantion: Supplementary data are available at Bioinformatics online.Mesh:
Year: 2017 PMID: 28172632 PMCID: PMC6075182 DOI: 10.1093/bioinformatics/btw627
Source DB: PubMed Journal: Bioinformatics ISSN: 1367-4803 Impact factor: 6.937