szsctt / courses_cmri_r Goto Github PK

Useful links:

• Data analysis and visuzliation in R for Ecologists
• R for genomics
• R for reproducilbe scientific analysis
• Tips and tricks for teaching R
• One-page summary of R commands
• Rmarkdown cookbook

Workshop for introductory R analysis for people at CMRI - TVRU, GTRU?

Ideally one day's worth of material - two sessions, could be spread over one day.

Consider covering:

• Rstudio basics
• git
• conda?
• R basics
• tidyverse:
  • readr / vroom
  • dplyr / dtplyr
    • mutate
    • slice
    • filter
    • joins
  • ggplot2 / patchwork / cowplot
  • stringr?
• bioconductor: what is bioconductor, biostrings?
• case study: peptide analysis

• projects
• panes
• installing packages
• Rmarkdown
• git in rstudio?
• getting help: vignettes, help (?func, help pane), stack overflow
• reprex

• comments
• types: numeric, string
• coercing types
• assignment and variables
• vectors/matrices/data.frame
• indexing
• control flow: if/else, for loops
• functions
  • inbuilt functions
  • writing own functions
• pipes
• libraries
• design principles for reproducibility
  • don't re-use code/repeat yourself
  • comment frequently
  • testing / unit tests
  • what output do you expect?
  • formatting and readability matters
  • consider package versions: conda / venv
  • consider paths of input/output files (here)

Cheatsheats

• read_tsv, read_csv, read_delim
• column types
• headers
• vroom for multiple files

• mutate
• slice
• grouping
• summarize
• joins
• pivot wide/long
• tidy select
• dtplyr / dbplyr / multidplyr

• aesthetics
• geoms
• facets
• scales
• labels
• annotation
• saving plots
• patchwork / cowplot

• stringr: regex
• glue
• purrr: map, reduce

• pheatmap
• rstatix

• intro to bioconductor
• biostrings
• edgeR / DEseq2
• seurat
• GenomicRanges
• karyoploteR