SEQualyzer: interactive tool for quality control and exploratory analysis of high-throughput RNA structural profiling data

Krishna Choudhary, Luyao Ruan, Fei Deng, Nathan Shih, Sharon Aviran

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)441-443
Number of pages3
JournalBioinformatics (Oxford, England)
Volume33
Issue number3
DOIs
StatePublished - Feb 1 2017

ASJC Scopus subject areas

  • Statistics and Probability
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Computational Mathematics

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