https://github.com/carinelegrand/RiboVIEW

Visualization, Quality and Statistics for Ribosome Profiling
https://github.com/carinelegrand/RiboVIEW

Last synced: about 1 month ago
JSON representation

Visualization, Quality and Statistics for Ribosome Profiling

• Host: GitHub
• URL: https://github.com/carinelegrand/RiboVIEW
• Owner: carinelegrand
• Created: 2019-10-29T18:52:11.000Z (about 5 years ago)
• Default Branch: master
• Last Pushed: 2020-07-14T12:03:50.000Z (over 4 years ago)
• Last Synced: 2024-08-05T15:04:26.485Z (5 months ago)
• Language: R
• Homepage:
• Size: 4.43 MB
• Stars: 5
• Watchers: 2
• Forks: 1
• Open Issues: 2
• Metadata Files:
  • Readme: README

Awesome Lists containing this project

• awesome-riboseq - Code

README

        
This is package RiboVIEW for Visualization, Quality and Statistics for Ribosome Profiling

Purpose : Ribosomes translate messenger RNAs (mRNAs) into proteins, and 

  ribosome profiling technique allows to retrieve those mRNAs fragments which are 

  under active translation in a ribosome. These mRNA fragments are then generally

  sequenced and further analysed for codon enrichment, translation efficiency, etc.

  In this package we provide tools to compute and visualize results, perform 

  quality control, and derive an unbiased estimate of codon enrichment. 

  We offer the user a webpage view to scan own data on the following aspects: 

  periodicity, ligation and digestion of ribosome-protected footprints;

  reproducibility and batch effects of replicates; drugs-related artifacts;

  codon enrichment including variability observed between mRNAs and positions

  for ribosome acceptor, peptidyl and exit (A, P and E, respectively) sites ;

  mining of causal or confounding factors. 

  Reference : Legrand, C. and Tuorto, F. (in press) RiboVIEW: a computational 

  framework for visualization, quality control and statistical analysis of 

  ribosome profiling data, Nucleic Acids Research, doi : 10.1093/nar/gkz1074.

  (URL of advance article, online 28.11.2019 :

  https://academic.oup.com/nar/advance-article/doi/10.1093/nar/gkz1074/5645003)

Installation : From R, install devtools package if you don't already have it installed :

    install.packages("devtools")

Then, import the just installed library :

    library(devtools)

    

Finally, install RiboVIEW from its github repositery :

    install_github("carinelegrand/RiboVIEW")