analyseBranchPoint: Analyse branch point.

View source: R/TrajectoryGeometry.R

analyseBranchPointR Documentation

Analyse branch point.

Description

This function takes a single cell trajectory and analyses it starting from successively later points in pseudotime, with the rationale that a more consistent directionality will be followed after the branch point.

Usage

analyseBranchPoint(
  attributes,
  pseudotime,
  randomizationParams,
  statistic,
  start = (max(pseudotime) - min(pseudotime)) * 0.25,
  stop = (max(pseudotime) - min(pseudotime)) * 0.75,
  step = (max(pseudotime) - min(pseudotime)) * 0.05,
  nSamples = 1000,
  nWindows = 10,
  d = ncol(attributes),
  N = 1
)

Arguments

attributes

- An n x d (cell x attribute) matrix of numeric attributes for single cell data. Rownames should be cell names.

pseudotime

- A named numeric vector of pseudotime values for cells.

randomizationParams

- A character vector which is used to control the production of randomized paths for comparison.

statistic

- Allowable values are 'median', 'mean' or 'max'.

start

- The first pseudotime value (percentage of the trajectory) from which to analyse the trajectory from. Defaults to 25% of the way through the trajectory.

stop

- The last pseudotime value (as a percentage of the trajectory) from which to analyse the trajectory from. Defaults to 75% of the way through the trajectory.

step

- The size of the step to take between successively later starting points in pseudotime. Defaults to 5% of the trajectory length.

nSamples

- The number of sampled paths to generate (defaults to 1000).

nWindows

- The number of windows pseudotime should be split into to sample cells from (defaults to 10).

d

- The dimension under consideration. This defaults to ncol(attributes).

N

- The number of random paths to generated for statistical comparison to the given path (defaults to 1000).

Value

This returns a list of results for analyseSingleCellTrajectory, named by trajectory starting point. Each result from analyseSingleCellTrajectory is a list which contains an entry for each sampled path. Each of these entries is a list containing information comparing the sampled path in question to random paths. The entries consist of: pValue - the p-value for the path and statistic in question; sphericalData - a list containing the projections of the path to the sphere, the center of that sphere and the statistic for distance to that center; randomDistances - the corresponding distances for randomly chosen; paths; randomizationParams - the choice of randomization parameters

Examples

chol_branch_point_results = analyseBranchPoint(chol_attributes[,seq_len(3)],
                         chol_pseudo_time[!is.na(chol_pseudo_time)],
                         randomizationParams = c('byPermutation',
                                         'permuteWithinColumns'),
                         statistic = "mean",
                         start = 0,
                         stop = 50,
                         step = 5,
                         nSamples = 10,
                         N = 1)

AnnaLaddach/TrajectoryGeometry documentation built on Oct. 14, 2022, 10:27 a.m.