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Computational methods for ribosome profiling data analysis
Kiniry, Stephen J.; Michel, Audrey M.; Baranov, Pavel V.
Since the introduction of the ribosome profiling technique in 2009 its popularity has greatly increased. It is widely used for the comprehensive assessment of gene expression and for studying the mechanisms of regulation at the translational level. As the number of ribosome profiling datasets being produced continues to grow, so too does the need for reliable software that can provide answers to the biological questions it can address. This review describes the computational methods and tools that have been developed to analyze ribosome profiling data at the different stages of the process. It starts with initial routine processing of raw data and follows with more specific tasks such as the identification of translated open reading frames, differential gene expression analysis, or evaluation of local or global codon decoding rates. The review pinpoints challenges associated with each step and explains the ways in which they are currently addressed. In addition it provides a comprehensive, albeit incomplete, list of publicly available software applicable to each step, which may be a beneficial starting point to those unexposed to ribosome profiling analysis. The outline of current challenges in ribosome profiling data analysis may inspire computational biologists to search for novel, potentially superior, solutions that will improve and expand the bioinformatician's toolbox for ribosome profiling data analysis.
Keyword(s): mRNA translation; Protein synthesis; Ribosome profiling; Translatome; Ribo‐Seq
Publication Date:
Type: Journal article
Peer-Reviewed: Yes
Language(s): English
Institution: University College Cork
Funder(s): Science Foundation Ireland; Health Research Board
Citation(s): Kiniry, S. J., Michel, A. M. and Baranov, P. V. (2019) 'Computational methods for ribosome profiling data analysis', Wiley Interdisciplinary Reviews RNA, e1577. doi: 10.1002/wrna.1577
Publisher(s): John Wiley & Sons, Inc.
File Format(s): application/pdf
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First Indexed: 2019-12-19 06:58:17 Last Updated: 2019-12-19 06:58:17