topologyTest {condiments} | R Documentation

## Differential Topology Test

### Description

Test whether or not slingshot should be fitted independently for different conditions or not.

### Usage

    topologyTest(sds, ...)

    ## S4 method for signature 'SlingshotDataSet'
    topologyTest(
      sds,
      conditions,
      rep = 100,
      threshs = 0.01,
      methods = ifelse(dplyr::n_distinct(conditions) == 2, "KS_mean", "Classifier"),
      parallel = FALSE,
      BPPARAM = BiocParallel::bpparam(),
      args_mmd = list(),
      args_classifier = list(),
      args_wass = list(),
      nmax = nrow(slingshot::slingPseudotime(sds))
    )

    ## S4 method for signature 'SingleCellExperiment'
    topologyTest(
      sds,
      conditions,
      rep = 100,
      threshs = 0.01,
      methods = ifelse(dplyr::n_distinct(conditions) == 2, "KS_mean", "Classifier"),
      parallel = FALSE,
      BPPARAM = BiocParallel::bpparam(),
      args_mmd = list(),
      args_classifier = list(),
      args_wass = list(),
      nmax = ncol(sds)
    )

    ## S4 method for signature 'PseudotimeOrdering'
    topologyTest(
      sds,
      conditions,
      rep = 100,
      threshs = 0.01,
      methods = ifelse(dplyr::n_distinct(conditions) == 2, "KS_mean", "Classifier"),
      parallel = FALSE,
      BPPARAM = BiocParallel::bpparam(),
      args_mmd = list(),
      args_classifier = list(),
      args_wass = list(),
      nmax = nrow(slingshot::slingPseudotime(sds))
    )

### Arguments

`sds` | A slingshot object already run on the full dataset. Can be either a `SlingshotDataSet` or a `SingleCellExperiment` object.
`...` | parameters including:
`conditions` | Either the vector of conditions, or a character indicating which column of the metadata contains this vector.
`rep` | How many permutations to run. Default to 50.
`threshs` | the threshold(s) for the KS test or classifier test. Default to .01 See `ks_test` and `classifier_test`.
`methods` | The method(s) to use to test. Must be among 'KS_mean', 'Classifier', "KS_all', "mmd' and 'wasserstein_permutation'. See details.
`parallel` | Logical, defaults to FALSE. Set to TRUE if you want to parallellize the fitting.
`BPPARAM` | object of class `bpparamClass` that specifies the back-end to be used for computations. See `bpparam` in `BiocParallel` package for details.
`args_mmd` | arguments passed to the mmd test. See `mmd_test`.
`args_classifier` | arguments passed to the classifier test. See `classifier_test`.
`args_wass` | arguments passed to the wasserstein permutation test. See `wasserstein_permut`.
`nmax` | How many samples to use to compute the mmd test. See details.

### Details

If there is only two conditions, default to 'KS_mean'. Otherwise, uses a classifier.

More than one method can be specified at once, which avoids running slingshot on the permutations more than once (as it is the slowest part).

For the 'mmd_test', if 'null=unbiased', it is recommand to set 'nmax=2000' or something of that order of magnitude to avoid overflowing the memory.

### Value

A list containing the following components:

- *method* The method used to test

- *thresh* The threshold (if relevant)

- *statistic* the value of the test statistic.

- *p.value* the p-value of the test.

### 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::getLineages(rd, cl)
    topologyTest(sds, condition, rep = 20)

[Package condiments version 1.0.0 Index]