Introduction to data analysis in R

Description

This is a short course on data analysis in R. The goal is to get the participants familiar with R code and to appreciate it as a tool to handle common experimental data. The materials are delivered in the form of lectures and interactive exercises.

Objectives

• To get familiar with R as a tool for data analysis
• To apply basic arithmetic and statistics in R
• To learn to handle experimental data in R (qPCR and images)

Format

Each module is delivered in three steps

• lectures/: slides discussing the main concepts
• practice/: interactive exercises for practicing purposes
• homework/: more exercises to test understanding

Outline

• Getting started in R
  • Lecture (Slides)
  • Practice (Link)
  • Homework (Link)
• Basic statistics in R
  • Lecture (Slides)
  • Practice (Link)
  • Homework (Link)
• Quantifying mRNA using the pcr package
  • Lecture (Slides)
  • Practice (Link)
  • Homework (Link)
• Quantifying protein co-localization in fluorescence images using the colocr package
  • Lecture (Slides)
  • Practice (Link)
  • Homework (Link)

Readings

• Tidy data by Hadley Wickham (Link)
• Ahmed M, Kim DR. pcr: an R package for quality assessment, analysis and testing of qPCR data. PeerJ. 2018 Mar 16;6:e4473. doi: 10.7717/peerj.4473.
• Ahmed M, Lai TH, Kim DR. colocr: an R package for conducting co-localization analysis on fluorescence microscopy images. PeerJ. 2019;7:e7255. doi:10.7717/peerj.7255

Resources (what to learn next?)

• Introduction to R (Data Camp Free Interactive Course)
• Intermediate R Course (Data Camp Free Interactive Course)
• R for Data Science (Book)