Description Usage Arguments Value Examples

View source: R/TrajectoryGeometry.R

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.

1 2 3 4 5 6 7 8 9 10 11 12 13 | ```
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
)
``` |

`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). |

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

1 2 3 4 5 6 7 8 9 10 | ```
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)
``` |

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