README.md

iSEE custom panel

• Check extending iSEE at https://isee.github.io/iSEE-book/ for more details on the procedure to extend iSEE classes.

DifferentialAbundancePlot

• Produce barplots of the relative cell abundance between conditions, at the pseudo-replicate level and for each cluster/cell population separatly.
• The Cluster, Pseudoreplicate and Condition variables needs to be specify to initalize the app.
• In addition, if you are interested in only one part of your dataset (e.g. one genotype only), you can subset your inital data. To do so, you need to specify the group variable which contain the information about which cell belong to your sub-group of interest. In the app, you will be able to select which level of this group variable you would like to use to substract your dataset. If you do not want to subset your initial dataset, set Group to None.
• All variables need to be colnames of the colData of your sce object.
• Be aware that frequency are in percentage and that the scale is proper to each panel.

Deploy the app

If you want the entire dataset you need to set Group to None

library(iSEE)

sce <- ... # load singlecell object

source('DifferentialAbundancePlot.R')

initial = list()

initial[["DifferentialAbundancePlot1"]] <-
  new("DifferentialAbundancePlot",
      Cluster = 'cell_type_MouseRNAseqData', Condition = "SampleGroup",Pseudoreplicate = "SampleName",Group='None',
      PanelHeight = 400L, PanelWidth = 12L )


app <- iSEE(se=sce, initial = initial, colormap = ecm)

If you want only a subset of you dataset, you need to specify what is the Group variable

library(iSEE)

sce <- ... # load singlecell object

source('DifferentialAbundancePlot.R')

initial = list()

initial[["DifferentialAbundancePlot1"]] <-
  new("DifferentialAbundancePlot",
      Cluster = 'cell_type_MouseRNAseqData', Condition = "SampleGroup",Pseudoreplicate = "SampleName",Group='Mouse',
      PanelHeight = 400L, PanelWidth = 12L )

app <- iSEE(se=sce, initial = initial, colormap = ecm)