IR+ - Updated Inverted Repeat scoping tool

Link to the web application.

Table of Contents

• About the program and how to use it
  • How the project is divided
• Questions
• Reference
• Contact
• Acknowledgements

About the program and how to use it

IR+ is a tool for visualizing the genes and indel mismatches on the boundaries of the junction sites of the chloroplast genome.

You can either use the web application at https://irscope.shinyapps.io/IRplus/ or download the code from the repository and run it locally. In the latter case you will need to use R, RStudio and shiny. All other dependencies should get installed when starting the app. To run it you need to open the file app.R and press Run App or run shiny::runApp("/path/to/IRplus"). A GUI equal to the one at the web will appear and you can test everything manually.

How the project is divided

There are two main parts:

• Related to the Shiny app: app file to set up the UI and server for the web application.
• IRscope R package: in IRscope/ folder. It wraps all the functions used by the program to find the IR, mismatches and for the plotting. It contains several files:
  • imports: libraries used by the package.
  • read_gb_file: functions to fetch or read the gbfiles.
  • parse_gb_file: given the gb file or dogma file extracts the needed information.
  • process_data: main functions to calculate all the information needed for the plotting (IRs and IRsD).
  • gene_info: gets the information about the genes in the needed format.
  • detect_ir: functions to detect the IR and indel mismatches.
  • plot_genome: main functions to plot (IRs2 and IRs2D) and the needed auxiliar functions.

Questions

You can access the FAQ section from the Questions? section in the web app. If you don't find what you're looking for there, you can post an issue here.

Reference

Publication at Bioinformatics https://academic.oup.com/bioinformatics/article/34/17/3030/4961430.

Contact

• Ali Amiryousefi - ali.amiryousefi@helsinki.fi
• Carmen Diez - carmen.diezmenendez@estudiante.uam.es

Acknowledgements

• Chloroplot: visualizing organelle genomes.
• University of Helsinki.
• Freepik icons: SVG icons in Coloring section from Flaticon.