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Table of Contents

Software that we may utilise in different workflows (or access ARGUS for a desktop pre-installed with software)

1. Download and install R (latest stable version, or a specific version if needed) from here - https://www.r-project.org/
2. Download and install RStudio Desktop from here - https://www.rstudio.com/products/rstudio/#Desktop
3. Download and install Rtools (for package building from GitHub repositories) - https://cran.r-project.org/bin/windows/Rtools/
4. Download and install devtools (for package building from GitHub repositories - install.packages("devtools")
5. Download and install FlowJo from here (and organise a licence if you haven't already got one)
6. Download and install SeqGeq from here (and organise a licence if you haven't already got one)
7. Download and install Matlab

Excellent links for information that was used for R/Rstudio/flowCore

1. Basic intro to R - https://cran.r-project.org/doc/contrib/Torfs+Brauer-Short-R-Intro.pdf
2. Introduction to flowCore - https://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-10-106
3. R package vigenettes (which are the mini guides for each package developed in R)

Data pre-processing in FlowJo using R plugins

...

In FlowJo, after importing your cytometry data, click the 'Check sample quality' button in the tools workspace. This will flag samples that should be checked. FlowJo plots the median values for each parameter over time and flags any that are outside of 2 standard deviations. Green is good. Any thing else should be reviewed. 

Active sample quality check - FlowAI in FlowJo

...

• Have R installed (version >3.4)
• Install BioConductor & flowCore
  • source("https://bioconductor.org/biocLite.R")
  • biocLite()
  • biocLite("flowCore")
• Install PNG package
  • install.packages("png")
• Install flowAI
  • biocLite("flowAI")
• Install stringi (I required this package additionally)
  • biocLite("stringi")
• Load libraries in R
  • library(flowCore)
    library(stringi)
    library(flowAI)
• Have FlowJo installed with the correct R path in the preferences
  
• If not already present, download and move FlowAI.jar file into the FlowJo plugins folder (available from the FlowJo exchange)
• Restart FlowJo
• Select sample and navigate to Plugins, FlowAI. Select parameters and compute. Example output is shown below including layout depiction.
  
  

Active sample quality check - FlowClean in FlowJo

To enable FlowClean

• Have R installed (version >3.4)
• Install BioConductor
  • source("https://bioconductor.org/biocLite.R")
  • biocLite("flowCore")
  • biocLite("flowClean")
• Load libraries in R
  • library(flowCore)
    library(flowClean)
• Have FlowJo installed with the correct R path in the preferences
  
• If not already present, download and move FlowClean.jar file into the FlowJo plugins folder (available from the FlowJo exchange)
• Restart FlowJo
• Select sample and navigate to Plugins, FlowClean. Select parameters and compute. Example output is shown below.
  

Reading and analysing FCS files in R/RStudio

Please note I am no expert in R/RStudio and apologise in advance if my nomenclature or the below has errors.This is still under construction so please email me and we can update this guide ASAP.

...

1. Open RStudio (ensure you run as administrator, otherwise yo umay you may run into permission errors).

   Install Bioconductor and additional packages that are used for flow cytometry data analysis

   Code Block## try http:// if https:// URLs are not supported
2. Make a new project (a project can be considered a workspace where everything can be saved to)

3. Some basic packages/libraries should be installed while working with flow data, this list isn't comprehensive but it contains some useful basics. 

   Code Block
   source("https://bioconductor.org/biocLite.R") biocLite() biocLite(pkgs =c("flowCore",dependencies=TRUE) biocLite("FlowSOM","flowViz") biocLite(,"flowUtils") biocLite(,"geneplotter","Seurat","stringi","yaml","dplyr"), ask = FALSE) install.packages("stringi")

   Determine your working directory by entering 

   Code Block
   devtools",dependencies=TRUE,ask=FALSE) library(flowCore,flowViz,flowUtils,geneplotter,Seurat,dplyr,yaml,stringi,devtools)

   
   

   Note: There are many Vignettes in the packages which are ever so helpful. Vignettes are help guides that can help to show you how to use different tools/functions.
   
   

4. Some commonly used codes - good to get familiar with

   Code Block
   #gets to working directory getwd() #sets

   Set your

   the working

   directory by entering - for example

   Code Block
   directory setwd('C:/Users/utopi/Desktop/testdata')

   Set the FCS folder as a variable

   Code Block
   ##file.name #assign a file to a variable fileName <- system.file("extdata","0877408774.B08", package="flowCore")"C:/Users/utopi/Desktop/testdata/sample.fcs" #assign a folder to a variable folderName <- "C:/Users/utopi/Desktop/testdata/" #read a FCS file to a variable using read.FCS from flowCore data1 = read.FCS('A1.fcs')

5. Still in progress...

Example:

source("https://bioconductor.org/biocLite.R")

biocLite()

biocLite("flowCore",dependencies=TRUE)

1. #assign a variable an example data file i.e. from a vignette example fileName <- system.file("extdata","lymphocytes.fcs",package="FlowSOM")

   
   

2. Lets analyse some data..
3. Put your data in a folder on your computer
4. In RStudio go to file and then new R script (we will be writing the script so that we can rerun it if needed)
5. Lets assign the folder to a variable