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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

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  1. Open RStudio (ensure you run as administrator, otherwise you may run into permission errors).
  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("FlowSOM",dependencies=TRUE,suppressUpdates=TRUE)
    biocLite("flowCore",dependencies=TRUE,suppressUpdates=TRUE)
    biocLite("flowViz",dependencies=TRUE,suppressUpdates=TRUE)
    biocLite("flowUtils",dependencies=TRUE,suppressUpdates=TRUE)
    biocLite("geneplotter",dependencies=TRUE,suppressUpdates=TRUE)
    biocLite("Seurat",dependencies=TRUE,suppressUpdates=TRUE)
    biocLite("stringi",dependencies=TRUE,suppressUpdates=TRUE)
    biocLite("yaml",dependencies=TRUE,suppressUpdates=TRUE)
    biocLite("dplyr",dependencies=TRUE,suppressUpdates=TRUE)
    biocLite("openCyto",dependencies=TRUE,suppressUpdates=TRUE)
    biocLite("tsne",dependencies=TRUE,suppressUpdates=TRUE)
    biocLite("Rtsne",dependencies=TRUE,suppressUpdates=TRUE)
    biocLite("edgeR",dependencies=TRUE,suppressUpdates=TRUE)
    
    install.packages("dplyr",dependencies=TRUE,suppressUpdates=TRUE)
    install.packages("yaml",dependencies=TRUE,suppressUpdates=TRUE) 
    install.packages("devtools",dependencies=TRUE,suppressUpdates=TRUE)
    
    library(flowCore)
    library(FlowSOM)
    library(flowViz)
    library(flowUtils)
    library(geneplotter)
    library(Seurat)
    library(dplyr)
    library(yaml)
    library(stringi)
    library(openCyto)
    library(tsne)
    library(Rtsne)


    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 the working directory
    setwd('C:/Users/utopi/Desktop/testdata')
    #assign a file to a variable
    fileName <- "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')
    #assign a variable an example data file i.e. from a vignette example
    fileName <- system.file("extdata","lymphocytes.fcs",package="FlowSOM")


  5. Examples to try...
    flowClust workflow in vignette
    flowSOM workflow in vignette 
    openCyto workflow in vignette
    Rtsne - https://github.com/lmweber/FlowSOM-Rtsne-example


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

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