Generate bootstrap plots

Source: R/generate_bootstrap_plots_for_transcriptome.r

generate_bootstrap_plots_for_transcriptome takes a genelist and a single cell type transcriptome dataset and generates plots which show how the expression of the genes in the list compares to those in randomly generated gene lists

generate_bootstrap_plots_for_transcriptome(
  sct_data,
  tt,
  thresh = 250,
  annotLevel = 1,
  reps,
  full_results = NA,
  listFileName = "",
  showGNameThresh = 25,
  ttSpecies = "mouse",
  sctSpecies = "mouse",
  sortBy = "t",
  onlySignif = TRUE,
  savePath = tempdir()
)

Arguments

sct_data

List generated using generate_celltype_data.
tt

Differential expression table. Can be output of topTable function. Minimum requirement is that one column stores a metric of increased/decreased expression (i.e. log fold change, t-statistic for differential expression etc) and another contains gene symbols.
thresh

The number of up- and down- regulated genes to be included in each analysis (Default: 250)
annotLevel

an integer indicating which level of the annotation to analyse (Default: 1).
reps

Number of random gene lists to generate (Default: 100, but should be >=10,000 for publication-quality results).
full_results

The full output of ewce_expression_data for the same gene list.
listFileName

String used as the root for files saved using this function.
showGNameThresh

Integer. If a gene has over X percent of it's expression proportion in a cell type, then list the gene name
ttSpecies

Either 'mouse' or 'human' depending on which species the differential expression table was generated from
sctSpecies

Either 'mouse' or 'human' depending on which species the single cell data was generated from.
sortBy

Column name of metric in tt which should be used to sort up- from down- regulated genes (Default: "t").
onlySignif

Should plots only be generated for cells which have significant changes?
savePath

Directory where the BootstrapPlots folder should be saved, default is a temp directory.

Value

Saves a set of PDF files containing graphs and returns the file where they are saved. These will be saved with the filename adjusted using the value of listFileName. The files are saved into the BootstrapPlot folder. Files start with one of the following:

  • qqplot_noText: sorts the gene list according to how enriched it is in the relevant cell type. Plots the value in the target list against the mean value in the bootstrapped lists.

  • qqplot_wtGSym: as above but labels the gene symbols for the highest expressed genes.

  • bootDists: rather than just showing the mean of the bootstrapped lists, a boxplot shows the distribution of values

  • bootDists_LOG: shows the bootstrapped distributions with the y-axis shown on a log scale

Examples

if (FALSE) {
## Load the single cell data
ctd <- ewceData::ctd()

## Set the parameters for the analysis
## Use 3 bootstrap lists for speed, for publishable analysis use >10,000
reps <- 3
annotLevel <- 1 # <- Use cell level annotations (i.e. Interneurons)
## Use 5 up/down regulated genes (thresh) for speed, default is 250
thresh <- 5

## Load the top table
tt_alzh <- ewceData::tt_alzh()

tt_results <- EWCE::ewce_expression_data(
    sct_data = ctd,
    tt = tt_alzh,
    annotLevel = 1,
    thresh = thresh,
    reps = reps,
    ttSpecies = "human",
    sctSpecies = "mouse"
)

## Bootstrap significance test,
## no control for transcript length or GC content
full_results <- EWCE::generate_bootstrap_plots_for_transcriptome(
    sct_data = ctd,
    tt = tt_alzh,
    thresh = thresh,
    annotLevel = 1,
    full_results = tt_results,
    listFileName = "examples",
    reps = reps,
    ttSpecies = "human",
    sctSpecies = "mouse",
    savePath = tempdir()
)
}