R Help
Installing and loading R packages¶
Repositories¶
- CRAN - official R repository
- Bioconductor - topic specific repository
- Github - most popular repository for open source projects but not R specific
Package Installation¶
The commands for the installation of R packages depends on the repository.
### CRAN repository : install.packages("package") install.packages(c("packageA", "packageB")) ### Bioconductor: ## R version 3.6+ if (!requireNamespace("BiocManager", quietly = TRUE)) install.packages("BiocManager") BiocManager::install("package") ## Older R versions source("https://bioconductor.org/biocLite.R") biocLite("package") ### GitHub library(devtools) devtools::install_github("link/to/package")
Package Info¶
It is always a good idea to look at the basic information about a package maybe before but certainly after you have installed it.
packageDescription("package") help(package = "package")
Manage Packages¶
# List all installed packages installed.packages() # Get Package version packageVersion("fun") # Update a package update.packages("fun") # Load a package library("fun") # Un-load a package detach("package:fun", unload=TRUE) # Remove a package remove.packages("fun")
Example(s)¶
## Alternative package version # Install dplyr by installing tidyverse (collection of data science tools): install.packages("tidyverse") search() # Alternatively, install just dplyr: install.packages("dplyr") # Or the development version from GitHub: install.packages("devtools") devtools::install_github("tidyverse/dplyr") ## Load multiple CRAN packages (version A) # Package list package.list = c("ggplot2","RColorBrewer","ggpubr") package.manager <- lapply( package.list, FUN <- function(x) { # Load multiple packages and # install missing packages if (!require(x, character.only = TRUE)) { install.packages(x, dependencies = TRUE) library(x, character.only = TRUE) } } ) ## Load multiple CRAN packages (version B) # An R function provided by Steven Worthington (https://gist.github.com/stevenworthington) # In a fist step, the fuction checks if the package is installed. Install the package if not installed, then load the package into the R session. ipak <- function(pkg){ new.pkg <- pkg[!(pkg %in% installed.packages()[, "Package"])] if (length(new.pkg)) install.packages(new.pkg, dependencies = TRUE) sapply(pkg, require, character.only = TRUE) } packages <- c("ape","vegan","ggplot","tidyverse","plotly","gridExtra","igraph","RColorBrewer") ipak(packages)
R Code with Style¶
Style Guides¶
Style Packages¶
-
styler -
install.packages("styler")
-
lintr -
devtools::install_github("jimhester/lintr")
-
formatR / Help with formatR -
install.packages("formatR")
Code Folding¶
RStudio supports both automatic and user-defined folding for regions of code. Code folding allows you to easily show and hide blocks of code to make it easier to navigate your source file and focus on the coding task at hand.
To insert a new code section you can use the Code > Insert Section command. Alternatively, any comment line which includes at least four trailing dashes (-), equal signs (=), or pound signs (#) automatically creates a code section.
## Setup ---- ## clean/reset environment rm(list=ls()) ## R and Bioconductor libraries library(ggplot2) ## Data Import ---- otufile <- "ZOTU_c99_Count_Sintax.txt" mapfile <- "MapFile.txt" ## Import into Phyloseq d.ZOTU <- import_qiime(otufilename = otufile, mapfilename = mapfile) d.ZOTU
Cheat-Sheets PDFs¶
- R Base (3/15)
- R Data Import (8/19)
- R Data Table (1/19)
- R Data Transformation (8/19)
- RMarkdown Reference Guide (10/14)
- RMarkdown Cheat Sheet (2/16)
- R Data Visualization with ggplot2 (12/19)