Flow Cytometry Analysis

Usage

To use the code for each of the chapters detailed below the following packages need to be installed. The code below will install, where needed, and load all of the required packages.

# Install CRAN packages
pkgs <- c('ggplot2', 'grid', 'reshape', 'scales', 'bmp',
          'RColorBrewer', 'SDMTools', 'stargazer', 'devtools',
          'rpart', 'rattle', 'rpart.plot')
pkgs_not_installed <- pkgs[!(pkgs %in% installed.packages())]
for (pkg in pkgs_not_installed) {
  install.packages(pkg, dependencies = TRUE, 
                   character.only = TRUE, type = 'binary')
}

# Install FlowClust
devtools::install_bioc('flowClust', type = 'binary')

# Load all packages
lapply(c(pkgs, 'flowClust'), library, character.only = TRUE)

Additionally, to remove scientific notation of the numeric display values run:

options(scipen = 9999)

Chapter 1: Introduction

Produces a plot which displays:

1. Rituximab data;
2. Subjective Manual Gating;
3. FlowClust Gating;
4. Lattice Structure of data;
5. Probability Map using Multi-Resolution Analysis;
6. Clusters using Multi-Resolution Analysis.

Chapter 2: Flow Cytometry

Produces plots of flowClust clustering on the Rituximab and GvHD Control cytometry datasets.

Chapter 3: Bernoulli Random Variables

Introduces the Generalised Binomial distribution with functions to compute PDF, CDF, quantiles and random samples. Generates plots which display:

• properties of the Generalised Binomial Distribution;
• statistical properties of the distribution for given sized structures;
• compare analytical and simulation results;

Note: the code in this file will take considerable time to run since the simulations are considerably large.

Chapter 4: Adapted MCMC

Using MCMC methods, and the methodology derived in Chapter 3 to clean and segment two image files.

Chapter 5: Hierarchical Approach

Implementing multi-resolution components on top of the core methodology of Chapter 3 and the adapted MCMC approach of Chapter 4.

Chapter 6: Application to Flow Cytometry

Applies the methods discussed and shown in Chapters 3, 4, and 5 to the rituximab and GvHD positive and control flow cyotometry samples. A comparison to the methods of Lo et al. is also included.