working with biological data with R workshop

Workshop links - https://anatmela.github.io/20250407-RWorkshop/

Share document - https://etherpad.opendev.org/p/rworkshop20250407

Carpentries code of conduct - https://docs.carpentries.org/policies/coc/

R

Rstudio

Software carpentry - code of conduct

https://docs.carpentries.org/policies/coc/

Software carpentry - The ‘sticky notes’ system

What is R good for?

• Reproduicibility
  
• Efficiency
• Flexibility
  
• Systematic
  
• Collabortive

What can I do with R?

• Data manipulation (filter, sort, etc)
• Data visualisation
• Statistics

Cautionary tale…

What else can I do with R?

• Complex plots and graphs
  
• Work with biological sequence data and reference data (e.g. Bioconductor)

http://www.sthda.com/english/wiki/ggbio-visualize-genomic-data

What else can I do with R?

• Complex plots and graphs
  
• Work with biological data (e.g. Bioconductor)
  
• Work with Chemical data (e.g. ChemmineR)

https://www.bioconductor.org/packages/devel/bioc/vignettes/ChemmineR/inst/doc/ChemmineR.html

What else can I do with R?

• Complex plots and graphs
  
• Work with biological data (e.g. Bioconductor)
  
• Work with Chemical data (e.g. ChemmineR)
  
• Work with Economical data
  
• Create apps (Shiny)
• Interact with other software and different formats
• Write reports and presentations
  
• Statistical learning
• Web scraping
  
• Send emails
  
• SO MUCH MORE…

RXKCD

xkcd <- getXKCD('1168')

working with biological data with R workshop

Workshop links - https://anatmela.github.io/20250407-RWorkshop/

Share document - https://etherpad.opendev.org/p/rworkshop20250407

Carpentries code of conduct - https://docs.carpentries.org/policies/coc/

R

Rstudio

Data types

The type of data you are trying to interpret will determine which plot type you should use and which statistical tests may be informative.

https://youtu.be/7bsNWq2A5gI

ggplot

create graphics from your data by adding layers

ggplot(data, mapping = aes()) +                   # initialise

geom_<geom name>() +                            # actual type of plot (can have > 1)

scale_<which scale>_<type of data>           # optional (can set for each scale in aes)

other layers which can be added (used for further refinement of the plot):
- facets
- labs
- theme
- guides
- annotate