ArticleBioinformatics (Oxford, England)2017
SEQualyzer: interactive tool for quality control and exploratory analysis of high-throughput RNA structural profiling data.
Article in Bioinformatics (Oxford, England), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- A Workflow for Identifying Helicase-Dependent RNA Structural Changes in Transcriptional Termination: From DMS Sequencing Analysis to Reporter Assay-Based Validation.Methods in molecular biology (Clifton, N.J.) · 2027Article
- dStruct: identifying differentially reactive regions from RNA structurome profiling data.Genome biology · 2019Article
- High-throughput determination of RNA structures.Nature reviews. Genetics · 2018Review
- Probing of RNA structures in a positive sense RNA virus reveals selection pressures for structural elements.Nucleic acids research · 2018Article
- Statistical modeling of RNA structure profiling experiments enables parsimonious reconstruction of structure landscapes.Nature communications · 2018Article
- Comparative and integrative analysis of RNA structural profiling data: current practices and emerging questions.Quantitative biology (Beijing, China) · 2017Article
Corrections and comments
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Authors and funding
5 authors.
Funding
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.
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Registered trials
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