ti_urd: URD

In dynverse/dynmethods: A collection of trajectory inference methods

URD

Description

Will generate a trajectory using URD.

This method was wrapped inside a container. The original code of this method is available here.

Usage

ti_urd(
  knn = 0L,
  sigma.use = 0,
  distance = "euclidean",
  n_floods = 20L,
  stability.div = 10L,
  mp.factor = 1L,
  perplexity = 30L,
  theta = 0.5,
  max_iter = 1000L,
  num.nn = 30L,
  do.jaccard = TRUE,
  optimal.cells.forward = 20L,
  max.cells.back = 40L,
  n.per.tip = 25000L,
  root.visits = 1L,
  max.steps = 25000L,
  n.subsample = 10L,
  divergence.method = "ks",
  cells.per.pseudotime.bin = 80L,
  bins.per.pseudotime.window = 5L,
  p.thresh = 0.01
)

Arguments

knn	Number of nearest neighbors to use. 0 takes a guess. Domain: U(0, 50). Default: 0. Format: integer.
sigma.use	Kernel width to use for the diffusion map. 0 uses destiny's global auto-detection procedure. Domain: U(0, 1). Default: 0. Format: numeric.
distance	Distance metric to use for determining transition probabilities. Domain: euclidean, cosine, rankcor. Default: euclidean. Format: character.
n_floods	Number of simulations to perform and average. Domain: U(5, 50). Default: 20. Format: integer.
stability.div	Number of simulation subsamplings to calculate. Domain: U(2, 50). Default: 10. Format: numeric.
mp.factor	Retain PCs than are this factor more than the estimated maximum singular value expected or random data. This is useful in cases when there are many PCs that have standard deviations just above that expected by random, which probably represent noise and should be excluded. Domain: U(0, 10). Default: 1. Format: numeric.
perplexity	Perplexity parameter for the tSNE. Domain: U(0, 100). Default: 30. Format: numeric.
theta	Speed/accuracy trade-off for Barnes-Hut approximation of tSNE. 0 is exact tSNE, higher is less accurate. Domain: U(0, 1). Default: 0.5. Format: numeric.
max_iter	Number of nearest neighbors to use. 0 takes a guess. Domain: e^U(4.61, 9.21). Default: 1000. Format: integer.
num.nn	How many nearest-neighbors to use in the k-nn graph. Domain: e^U(2.30, 4.61). Default: 30. Format: integer.
do.jaccard	Weight edges in the k-nn graph according to their Jaccard overlap?. Default: TRUE. Format: logical.
optimal.cells.forward	The number of cells in the direction specified by pseudotime.direction at which the logistic should reach 1-asymptote. Domain: e^U(1.61, 4.61). Default: 20. Format: numeric.
max.cells.back	The number of cells in the direction opposite from that specified by pseudotime.direction at which the logistic should reach asymptote. Domain: e^U(1.61, 5.30). Default: 40. Format: numeric.
n.per.tip	Number of walks to do per tip. Domain: e^U(4.61, 13.82). Default: 25000. Format: integer.
root.visits	Number of steps to take that visit a root.cell before stopping. Domain: U(1, 5). Default: 1. Format: integer.
max.steps	Number of walks to do per tip. Domain: e^U(4.61, 13.82). Default: 25000. Format: integer.
n.subsample	Number of subsamplings to perform for calculating stability. Domain: e^U(0.69, 4.61). Default: 10. Format: integer.
divergence.method	Distance metric to use for determining transition probabilities. Domain: ks, preference. Default: ks. Format: character.
cells.per.pseudotime.bin	Approximate number of cells to assign to each pseudotime bin for branchpoint finding. Domain: e^U(2.30, 6.91). Default: 80. Format: integer.
bins.per.pseudotime.window	Width of moving window in pseudotime used for branchpoint finding, in terms of bins. Domain: U(2, 20). Default: 5. Format: integer.
p.thresh	P-value threshold to use in determining whether visitation is significantly different from pairs of tips. Domain: e^U(-11.51, 0.00). Default: 0.01. Format: numeric.

Value

A TI method wrapper to be used together with infer_trajectory

References

Farrell, J.A., Wang, Y., Riesenfeld, S.J., Shekhar, K., Regev, A., Schier, A.F., 2018. Single-cell reconstruction of developmental trajectories during zebrafish embryogenesis. Science 360, eaar3131.

dynverse/dynmethods documentation built on Jan. 18, 2024, 4:44 a.m.