R_useful

Here is a repo with some R scripts or snippet useful ...

Tips

Below are some resources on R.

To learn R, there are some resources here :

• First, view the Packages (and their vignette) on the CRAN (https://cran.r-project.org/), Bioconductor (https://www.bioconductor.org/), and Github (https://github.com/)
• Also, see books :
• "One book to list them all" : https://www.bigbookofr.com/
• Hadley Wickham's books "R for Data Science" (2nde édition) : https://r4ds.hadley.nz/
• "Advanced R" : https://adv-r.hadley.nz/

Various websites, blogs, and forums:

• Some docs and helps : https://cran.r-project.org/other-docs.html
• frrrenchies : https://frrrenchies.github.io/frrrenchies/
• R Weekly : https://rweekly.org/
• A list of R conferences and meetings : https://jumpingrivers.github.io/meetingsR/events.html
• ThinkR : https://thinkr.fr/
• R bloggers : https://www.r-bloggers.com/
• R Open sci : https://ropensci.org/
• CRANberries aggregates information about new in CRAN : https://dirk.eddelbuettel.com/cranberries/
• Forum utilisateur R francais : https://forums.cirad.fr/logiciel-R/

Tidyverse or Data.Table : you have to choose

• data.table : https://riptutorial.com/data-table
• data.table cheat sheet : https://s3.amazonaws.com/assets.datacamp.com/img/blog/data+table+cheat+sheet.pdf
• Introduction R & tidyverse : https://juba.github.io/tidyverse/index.html
• ANF "Data Science avec R : tidyverse et ses différentes facettes" organised by RIS : https://ris.cnrs.fr/anf-data-science-avec-r-tidyverse-et-ses-differentes-facettes-2024/presentation-anf-tidyverse/

About reproductibility, check out this list :

• "renv" to manage library versions : https://rstudio.github.io/renv/articles/renv.html
• R project in Docker (example of presentation : https://m.canouil.dev/journey-reproducibility/#1 (https://github.com/mcanouil/journey-reproducibility ))
• If you work on server, look for Docker Dev containers : example of introduction : https://github.com/mboissel/Docker_useful
• or my feedback : https://github.com/mboissel/Presentations/blob/master/Docker_feedback_20230718_mboissel.pdf
• rix r pkg is also an alternative : https://github.com/ropensci/rix
• Be careful not to update blindly : https://brodrigues.co/posts/2025-06-21-ggplot4.html

Here are some resources for R analyses on omics or biological data :

• Book + TP "Modern Statistics for Modern Biology" : https://www.huber.embl.de/msmb/
• Computational Genomics with R : https://compgenomr.github.io/book/
• Anlayses Templates : https://github.com/mboissel/analysis-scripts-templates
• DESeq2 experimental design and interpretation : https://rstudio-pubs-static.s3.amazonaws.com/329027_593046fb6d7a427da6b2c538caf601e1.html
• mixOmics for multi omics analyses : http://mixomics.org/
• Biomart for annotation : https://docs.ropensci.org/biomartr/

Other resources ?

• If you want to play with Python via R see : https://rstudio.github.io/reticulate/
• If you want to play with many other languages via R (Rmarkdown, Rcpp, ...) : At this point, I recommend switching to VScode instead of Rstudio.
• Watch youtube chanel "useR! Conference" : https://www.youtube.com/channel/UCv_a9ZGZOH588wUZHZl6T_g/videos There you will find a wide variety of videos on R used in many different fields.
• https://www.r-project.org/conferences/
• Jenny Bryan's video (Rstudio) : https://www.youtube.com/watch?v=IzRn-QnOhug&ab_channel=RConsortium

Groups

• Rladies
• RUG (R User Group)
• Meetup (like in Paris https://www.meetup.com/fr-FR/rparis/)