progressionTest {condiments} | R Documentation |
Test whether or not the pseudotime distribution are identical within lineages between conditions
progressionTest(pseudotime, ...) ## S4 method for signature 'matrix' progressionTest( pseudotime, cellWeights, conditions, global = TRUE, lineages = FALSE, method = ifelse(dplyr::n_distinct(conditions) == 2, "KS", "Classifier"), thresh = ifelse(method == "Classifer", 0.05, 0.01), args_mmd = list(), args_classifier = list(), args_wass = list(), rep = 10000 ) ## S4 method for signature 'SlingshotDataSet' progressionTest( pseudotime, conditions, global = TRUE, lineages = FALSE, method = ifelse(dplyr::n_distinct(conditions) == 2, "KS", "Classifier"), thresh = ifelse(method == "Classifer", 0.05, 0.01), args_mmd = list(), args_classifier = list(), args_wass = list(), rep = 10000 ) ## S4 method for signature 'SingleCellExperiment' progressionTest( pseudotime, conditions, global = TRUE, lineages = FALSE, method = ifelse(dplyr::n_distinct(conditions) == 2, "KS", "Classifier"), thresh = ifelse(method == "Classifer", 0.05, 0.01), args_mmd = list(), args_classifier = list(), args_wass = list(), rep = 10000 ) ## S4 method for signature 'PseudotimeOrdering' progressionTest( pseudotime, conditions, global = TRUE, lineages = FALSE, method = ifelse(dplyr::n_distinct(conditions) == 2, "KS", "Classifier"), thresh = ifelse(method == "Classifer", 0.05, 0.01), args_mmd = list(), args_classifier = list(), args_wass = list(), rep = 10000 )
pseudotime |
Can be either a |
... |
parameters including: |
cellWeights |
If |
conditions |
Either the vector of conditions, or a character indicating which column of the metadata contains this vector. |
global |
If TRUE, test for all lineages simultaneously. |
lineages |
If TRUE, test for all lineages independently. |
method |
One of "KS", "Classifier", "mmd", "wasserstein_permutation" or "Permutation" for a permutation. See details. Default to KS if there is two conditions and to "Classifier" otherwise. |
thresh |
The threshold for the KS test or Classifier test.
Ignored if |
args_mmd |
arguments passed to the mmd test. See |
args_classifier |
arguments passed to the classifier test. See |
args_wass |
arguments passed to the wasserstein permutation test. See
|
rep |
Number of permutations to run. Ignored if |
For every lineage, we compare the pseudotimes of the cells from either conditions, using the lineage weights as observations weights.
If method = "KS"
, this uses the updated KS test,
see ks_test
for details.
If method = "Classifier"
, this uses a classifier to assess if
that classifier can do better than chance on the conditions
If method = "Permutation"
, the difference of weighted mean
pseudotime between condition is computed, and a p-value is found by
permuting the condition labels.
If method = "mmd"
, this uses the mean maximum discrepancies
statistics.
The p-value at the global level can be computed in two ways. method is "KS"
or
"Permutation"
, then the p-values are computed using stouffer's
z-score method, with the lineages weights acting as weights. Otherwise,
the test works on multivariate data and is applied on all pseudotime values.
A data frame with 3 columns:
lineage for individual lineages, the lineage number. For global,
"All"
.
p.value the pvalue for the test at the global or lineage level
statistic for individual lineages, either the modified KS statistic
if method = "KS"
, or the weighted difference of means, if
method = "Permutation"
. For the global test, the combined Z-score.
Stouffer, S.A.; Suchman, E.A.; DeVinney, L.C.; Star, S.A.; Williams, R.M. Jr. (1949). The American Soldier, Vol.1: Adjustment during Army Life. Princeton University Press, Princeton.
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) progressionTest(sds, condition)