Lesson 7

IS428 Visual Analytics for Business Intelligence

About

Weekly Session

Assignments

Visual Analytics Project

Course Resources

Visualising and Analysing Multivariate Data

Content

• Introduction to Multivariate Data
• Trellis
• Correlation Matrix
• Ternary Plot
• Glyphs or Star Plot
• Heatmap
• Parallel Coordinate Plot
• Treemap

Readings

Core Readings

• An Introduction to Visual Multivariate Analysis
• Corrgrams: Exploratory Displays for Correlation Matrices
• Ternary Plot
• Multivariate Data Glyphs
• Parallel Coordinates
• Wikipedia: Heatmap

Optional Readings

• The scatter-plot matrix: a great tool
• A Graphical Display of Large Correlation Matrices
• Ternary Diagram
• Reading a Ternary Diagram
• Multidimensional Detective
• Parallel Coordinates
• Multivariate Analysis Using Parallel Coordinates

R Methods

Ternary Plot

• R packages for creating ternary plot
  • Ternary, which employs the native plot functions;
  • Plotly, which uses a bespoke suite of plotting functions;
  • vcd, which contains the function ternaryplot;
  • ggtern, an extension to ggplot2.

Heatmap

• Using R to draw a Heatmap from Microarray Data
• R packages for creating heatmap
  • heatmap() [R base function, stats package]: Draws a simple heatmap.
  • heatmap.2() [gplots R package]: Draws an enhanced heatmap compared to the R base function.
  • pheatmap() [pheatmap R package]: Draws pretty heatmaps and provides more control to change the appearance of heatmaps.
  • Heatmap() [ComplexHeatmap R/Bioconductor package]: Draws, annotates and arranges complex heatmaps (very useful for genomic data analysis)
  • Superheatmap
  • d3heatmap() [d3heatmap R package]: Draws an interactive/clickable heatmap