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Beyond read-counts: Ribo-seq data analysis to understand the functions of the transcriptome

Official URL:https://doi.org/10.1016/j.tig.2017.08.003
PubMed:View item in PubMed
Creators Name:Calviello, L. and Ohler, U.
Journal Title:Trends in Genetics
Journal Abbreviation:Trends Genet
Date:5 September 2017
Keywords:Translation, Ribo-seq, Transcriptomics, Genomics, Bioinformatics
Abstract:By mapping the positions of millions of translating ribosomes in the cell, ribosome profiling (Ribo-seq) has established its role as a powerful tool to study gene expression. Several laboratories have introduced modifications to the experimental protocol and expanded the repertoire of biochemical methods to study translation transcriptome-wide. However, the diversity of protocols highlights a need for standardization. At the same time, different computational analysis strategies have used Ribo-seq data to identify the set of translated sequences with high confidence. In this review we present an overview of such methodologies, outlining their assumptions, data requirements, and availability. At the interface between RNA and proteins, Ribo-seq can complement data from multiple omics approaches, zooming in on the central role of translation in the molecular cell.
Publisher:Elsevier (The Netherlands)
Item Type:Review

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