RiboVIEW: a computational framework for visualization, quality control and statistical analysis of ribosome profiling data.

ABSTRACT: Recently, newly developed ribosome profiling methods based on high-throughput sequencing of ribosome-protected mRNA footprints allow to study genome-wide translational changes in detail. However, computational analysis of the sequencing data still represents a bottleneck for many laboratories. Further, specific pipelines for quality control and statistical analysis of ribosome profiling data, providing high levels of both accuracy and confidence, are currently lacking. In this study, we describe automated bioinformatic and statistical diagnoses to perform robust quality control of ribosome profiling data (RiboQC), to efficiently visualize ribosome positions and to estimate ribosome speed (RiboMine) in an unbiased way. We present an R pipeline to setup and undertake the analyses that offers

SUBMITTER: Legrand C 

PROVIDER: S-EPMC6954398 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature