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MIC training: Modern data analysis in R/RStudio

Presentation, the code, and exercises to accompany the MIC training at UniBe, November 3, 2020.

File description

  • presentation-main.Rpres and html - the main presentation with workshop lecture and exercises,
  • examples - code snippets and examples for the presentation,
  • practicals - data, presentation, and code for the practical session.

Required software

Please download the latest versions of the following:

  • R for macOS/Linux/Windows from here, version 4.0x.
  • The latest RStudio from here, version 1.3.x.

Required R packages

The workflow is written in R and takes advantage of RStudio notebooks. The analysis uses the following packages that need to be present in your RStudio installation:

  • R.utils for directly reading comressed files
  • magrittr for pipes (typically loaded by other packages)
  • data.table for fast processing of large datasets
  • readxl for reading Excel files
  • ggplot2 for plotting
  • imputeTS for data imputation such as interpolation of NA's
  • ggthemes for additional color schemes in ggplot
  • plotly for interactive plots
  • RColorBrewer for extended colour palettes
  • pheatmap for heatmap
  • heatmaply for interactive heatmaps
  • scales for percentages on y-axis in ggplots
  • factoextra for extracting and visualisation of the results of multivariate data analyses
  • NbClust for determining the best number of clusters
  • testthat for unit testing
  • profvis for profiling
  • foreach with extension of the for loop
  • doParallel for parallel computations
  • optparse for command-line parameters

Install these packages by typing the following line in the R command-line interface:

  "data.table", "tidyverse",
  "readxl", "R.utils",
  "ggplot2", "plotly",
  "pheatmap", "heatmaply",
  "dendextend", "RColorBrewer", "scales",
  "factoextra", "NbClust",
  "testthat", "profvis",
  "foreach", "doParallel",

Alternatively, you can install packages using RStudio GUI by going to Tools > Install packages...


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