XPRESSyourself: Enhancing, standardizing, and automating ribosome profiling computational analyses yields improved insight into data

Ribosome profiling, an application of nucleic acid sequencing for monitoring ribosome activity, has revolutionized our understanding of protein translation dynamics. This technique has been available for a decade, yet the current state and standardization of publicly available computational tools fo...

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Bibliographic Details
Published in:PLoS computational biology 2020-01, Vol.16 (1), p.e1007625-e1007625
Main Authors: Berg, Jordan A, Belyeu, Jonathan R, Morgan, Jeffrey T, Ouyang, Yeyun, Bott, Alex J, Quinlan, Aaron R, Gertz, Jason, Rutter, Jared
Format: Article
Language:English
Subjects:
Automation
Biochemistry
Biology and Life Sciences
Computational Biology - methods
Computational neuroscience
Computer and Information Sciences
Computer programs
Data analysis
Databases, Genetic
Datasets
Efficiency
Engineering and Technology
HEK293 Cells
High-Throughput Nucleotide Sequencing - methods
Humans
Internet
Methods
Neuroprotection
Nucleic acids
Phenotypes
Protein Biosynthesis - genetics
Quality control
Reproducibility
Reproducibility of Results
Research and Analysis Methods
Ribosomes - genetics
RNA - genetics
Sequence Analysis, RNA - methods
Software
Software packages
Source code
Standardization
Supervision
Translation
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Description
Summary:Ribosome profiling, an application of nucleic acid sequencing for monitoring ribosome activity, has revolutionized our understanding of protein translation dynamics. This technique has been available for a decade, yet the current state and standardization of publicly available computational tools for these data is bleak. We introduce XPRESSyourself, an analytical toolkit that eliminates barriers and bottlenecks associated with this specialized data type by filling gaps in the computational toolset for both experts and non-experts of ribosome profiling. XPRESSyourself automates and standardizes analysis procedures, decreasing time-to-discovery and increasing reproducibility. This toolkit acts as a reference implementation of current best practices in ribosome profiling analysis. We demonstrate this toolkit's performance on publicly available ribosome profiling data by rapidly identifying hypothetical mechanisms related to neurodegenerative phenotypes and neuroprotective mechanisms of the small-molecule ISRIB during acute cellular stress. XPRESSyourself brings robust, rapid analysis of ribosome-profiling data to a broad and ever-expanding audience and will lead to more reproducible and accessible measurements of translation regulation. XPRESSyourself software is perpetually open-source under the GPL-3.0 license and is hosted at https://github.com/XPRESSyourself, where users can access additional documentation and report software issues.
ISSN:1553-7358
1553-734X
1553-7358
DOI:10.1371/journal.pcbi.1007625