Differential Differentiation Test

Test whether or not the cell repartition between lineages is independent of the conditions

differentiationTest(cellWeights, ...)

# S4 method for matrix
differentiationTest(
  cellWeights,
  conditions,
  global = TRUE,
  pairwise = FALSE,
  method = c("Classifier", "mmd", "wasserstein_permutation"),
  classifier_method = "rf",
  thresh = 0.01,
  args_classifier = list(),
  args_mmd = list(),
  args_wass = list()
)

# S4 method for SlingshotDataSet
differentiationTest(
  cellWeights,
  conditions,
  global = TRUE,
  pairwise = FALSE,
  method = c("Classifier", "mmd", "wasserstein_permutation"),
  classifier_method = "rf",
  thresh = 0.01,
  args_classifier = list(),
  args_mmd = list(),
  args_wass = list()
)

# S4 method for SingleCellExperiment
differentiationTest(
  cellWeights,
  conditions,
  global = TRUE,
  pairwise = FALSE,
  method = c("Classifier", "mmd", "wasserstein_permutation"),
  classifier_method = "rf",
  thresh = 0.01,
  args_classifier = list(),
  args_mmd = list(),
  args_wass = list()
)

# S4 method for PseudotimeOrdering
differentiationTest(
  cellWeights,
  conditions,
  global = TRUE,
  pairwise = FALSE,
  method = c("Classifier", "mmd", "wasserstein_permutation"),
  classifier_method = "rf",
  thresh = 0.01,
  args_classifier = list(),
  args_mmd = list(),
  args_wass = list()
)

Arguments

cellWeights	Can be either a SlingshotDataSet, a SingleCellExperiment object or a matrix of cell weights defining the probability that a cell belongs to a particular lineage. Each row represents a cell and each column represents a lineage. If only a single lineage, provide a matrix with one column containing all values of 1.
...	parameters including:
conditions	Either the vector of conditions, or a character indicating which column of the metadata contains this vector
global	If TRUE, test for all pairs simultaneously.
pairwise	If TRUE, test for all pairs independently.
method	One of "Classifier" or "mmd".
classifier_method	The method used in the classifier test. Default to "rf", i.e random forest.
thresh	The threshold for the classifier test. See details. Default to .05.
args_classifier	arguments passed to the classifier test. See classifier_test.
args_mmd	arguments passed to the mmd test. See mmd_test.
args_wass	arguments passed to the wasserstein permutation test. See wasserstein_permut.

Value

A data frame with 3 columns:

• *pair* for individual pairs, the lineages numbers. For global, "All".

• *p.value* the pvalue for the test at the global or pair level

• *statistic* The classifier accuracy

Examples

data('slingshotExample', package = "slingshot")
rd <- slingshotExample$rd
cl <- slingshotExample$cl
condition <- factor(rep(c('A','B'), length.out = nrow(rd)))
condition[110:139] <- 'A'
sds <- slingshot::slingshot(rd, cl)
differentiationTest(sds, condition)
#> note: only 1 unique complexity parameters in default grid. Truncating the grid to 1 .
#> 
#> Loading required package: lattice
#> Loading required package: ggplot2
#> note: only 1 unique complexity parameters in default grid. Truncating the grid to 1 .
#> 
#> # A tibble: 1 x 3
#>   pair  statistic p.value
#>   <chr>     <dbl>   <dbl>
#> 1 1vs2      0.552   0.298