Inferring a trajectory inference using Projected Slingshot

Will generate a trajectory using Projected Slingshot.

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

ti_projected_slingshot(shrink = 1, reweight = TRUE, reassign = TRUE,
  thresh = 0.001, maxit = 10L, stretch = 2,
  smoother = "smooth.spline", shrink.method = "cosine",
  run_environment = NULL)

Arguments

shrink	numeric; Logical or numeric between 0 and 1, determines whether and how much to shrink branching lineages toward their average prior to the split. (default: 1; range: from 0 to 1)
reweight	logical; Logical, whether to allow cells shared between lineages to be reweighted during curve-fitting. If TRUE, cells shared between lineages will be weighted by: distance to nearest curve / distance to curve.
reassign	logical; Logical, whether to reassign cells to lineages at each iteration. If TRUE, cells will be added to a lineage when their projection distance to the curve is less than the median distance for all cells currently assigned to the lineage. Additionally, shared cells will be removed from a lineage if their projection distance to the curve is above the 90th percentile and their weight along the curve is less than 0.1.
thresh	numeric; Numeric, determines the convergence criterion. Percent change in the total distance from cells to their projections along curves must be less than thresh. Default is 0.001, similar to principal.curve. (default: 0.001; range: from 1e-05 to 1e+05)
maxit	integer; Numeric, maximum number of iterations, see principal.curve. (default: 10L; range: from 0L to 50L)
stretch	numeric; Numeric factor by which curves can be extrapolated beyond endpoints. Default is 2, see principal.curve. (default: 2; range: from 0 to 5)
smoother	discrete; Choice of scatter plot smoother. Same as principal.curve, but "lowess" option is replaced with "loess" for additional flexibility. (default: "smooth.spline"; values: "smooth.spline", "loess", "periodic.lowess")
shrink.method	discrete; Character denoting how to determine the appropriate amount of shrinkage for a branching lineage. Accepted values are the same as for kernel in density() (default is "cosine"), as well as "tricube" and "density". See 'Details' for more. (default: "cosine"; values: "cosine", "tricube", "density")
run_environment	In which environment to run the method, can be "docker" or "singularity".

Value

A TI method wrapper to be used together with infer_trajectory