Reproducible analysis of sequencing-based RNA structure probing data with user-friendly tools
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Reproducible analysis of sequencing-based RNA structure probing data with user-friendly tools. / Kielpinski, Lukasz Jan; Sidiropoulos, Nikos; Vinther, Jeppe.
Structures of large RNA molecules and their complexes. ed. / Sarah A. Woodson; Frédéric H.T. Allain. Elsevier, 2015. p. 153-180 (Methods in Enzymology, Vol. 558).Research output: Chapter in Book/Report/Conference proceeding › Book chapter › Research › peer-review
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TY - CHAP
T1 - Reproducible analysis of sequencing-based RNA structure probing data with user-friendly tools
AU - Kielpinski, Lukasz Jan
AU - Sidiropoulos, Nikos
AU - Vinther, Jeppe
PY - 2015
Y1 - 2015
N2 - RNA structure-probing data can improve the prediction of RNA secondary and tertiary structure and allow structural changes to be identified and investigated. In recent years, massive parallel sequencing has dramatically improved the throughput of RNA structure probing experiments, but at the same time also made analysis of the data challenging for scientists without formal training in computational biology. Here, we discuss different strategies for data analysis of massive parallel sequencing-based structure-probing data. To facilitate reproducible and standardized analysis of this type of data, we have made a collection of tools, which allow raw sequencing reads to be converted to normalized probing values using different published strategies. In addition, we also provide tools for visualization of the probing data in the UCSC Genome Browser and for converting RNA coordinates to genomic coordinates and vice versa. The collection is implemented as functions in the R statistical environment and as tools in the Galaxy platform, making them easily accessible for the scientific community. We demonstrate the usefulness of the collection by applying it to the analysis of sequencing-based hydroxyl radical probing data and comparing different normalization strategies.
AB - RNA structure-probing data can improve the prediction of RNA secondary and tertiary structure and allow structural changes to be identified and investigated. In recent years, massive parallel sequencing has dramatically improved the throughput of RNA structure probing experiments, but at the same time also made analysis of the data challenging for scientists without formal training in computational biology. Here, we discuss different strategies for data analysis of massive parallel sequencing-based structure-probing data. To facilitate reproducible and standardized analysis of this type of data, we have made a collection of tools, which allow raw sequencing reads to be converted to normalized probing values using different published strategies. In addition, we also provide tools for visualization of the probing data in the UCSC Genome Browser and for converting RNA coordinates to genomic coordinates and vice versa. The collection is implemented as functions in the R statistical environment and as tools in the Galaxy platform, making them easily accessible for the scientific community. We demonstrate the usefulness of the collection by applying it to the analysis of sequencing-based hydroxyl radical probing data and comparing different normalization strategies.
U2 - 10.1016/bs.mie.2015.01.014
DO - 10.1016/bs.mie.2015.01.014
M3 - Book chapter
C2 - 26068741
AN - SCOPUS:84935016692
T3 - Methods in Enzymology
SP - 153
EP - 180
BT - Structures of large RNA molecules and their complexes
A2 - Woodson, Sarah A.
A2 - Allain, Frédéric H.T.
PB - Elsevier
ER -
ID: 154364159