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Reproducible Analysis of Sequencing-Based RNA Structure Probing Data with User-Friendly Tools
Lukasz Jan Kielpinski1, Nikolaos Sidiropoulos1, Jeppe Vinther1
1Section for RNA and Computational Biology, Department of Biology, University of Copenhagen, Copenhagen, Denmark.
Methods in Enzymology
|June 13, 2015
Summary
This study presents accessible tools for analyzing RNA structure probing data from high-throughput sequencing. These resources simplify the process, enabling researchers to investigate RNA structure and dynamics more effectively.
Area of Science:
- Molecular Biology
- Bioinformatics
- Computational Biology
Background:
- RNA structure probing experiments yield valuable data for predicting RNA secondary and tertiary structures.
- Massive parallel sequencing has increased experiment throughput but complicated data analysis for non-computational biologists.
- Analyzing RNA structure-probing data is crucial for identifying and investigating structural changes.
Purpose of the Study:
- To discuss strategies for analyzing massive parallel sequencing-based RNA structure-probing data.
- To provide accessible tools for reproducible and standardized analysis of this data.
- To facilitate the conversion of raw sequencing reads to normalized probing values and visualize results.
Main Methods:
- Development of a collection of tools implemented in the R statistical environment and Galaxy platform.
- Tools enable conversion of raw sequencing reads to normalized probing values using various published strategies.
- Includes functionalities for visualizing probing data in the UCSC Genome Browser and coordinate conversion.
Main Results:
- Demonstrated the utility of the tool collection using sequencing-based hydroxyl radical probing data.
- Compared different normalization strategies for RNA structure-probing data analysis.
- Provided a standardized workflow for processing and visualizing high-throughput RNA structure data.
Conclusions:
- The developed tool collection enhances accessibility for analyzing massive parallel sequencing-based RNA structure-probing data.
- Facilitates reproducible research and standardization in the field of RNA structure analysis.
- Empowers a broader scientific community to investigate RNA structure and dynamics without extensive computational expertise.
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