The main Haystack function

haystack(x, ...)

# S3 method for matrix
haystack(
  x,
  expression,
  weights.advanced.Q = NULL,
  dir.randomization = NULL,
  scale = TRUE,
  grid.points = 100,
  grid.method = "centroid",
  ...
)

# S3 method for data.frame
haystack(
  x,
  expression,
  weights.advanced.Q = NULL,
  dir.randomization = NULL,
  scale = TRUE,
  grid.points = 100,
  grid.method = "centroid",
  ...
)

# S3 method for Seurat
haystack(
  x,
  coord,
  assay = "RNA",
  slot = "data",
  dims = NULL,
  cutoff = 1,
  method = NULL,
  weights.advanced.Q = NULL,
  ...
)

# S3 method for SingleCellExperiment
haystack(
  x,
  assay = "counts",
  coord = "TSNE",
  dims = NULL,
  cutoff = 1,
  method = NULL,
  weights.advanced.Q = NULL,
  ...
)

Arguments

x: a matrix or other object from which coordinates of cells can be extracted.
...: further parameters passed down to methods.
expression: a matrix with expression data of genes (rows) in cells (columns)
weights.advanced.Q: If NULL naive sampling is used. If a vector is given (of length = no. of cells) sampling is done according to the values in the vector.
dir.randomization: If NULL, no output is made about the random sampling step. If not NULL, files related to the randomizations are printed to this directory.
scale: Logical (default=TRUE) indicating whether input coordinates in x should be scaled to mean 0 and standard deviation 1.
grid.points: An integer specifying the number of centers (gridpoints) to be used for estimating the density distributions of cells. Default is set to 100.
grid.method: The method to decide grid points for estimating the density in the high-dimensional space. Should be "centroid" (default) or "seeding".
coord: name of coordinates slot for specific methods.
assay: name of assay data for Seurat method.
slot: name of slot for assay data for Seurat method.
dims: dimensions from coord to use. By default, all.
cutoff: cutoff for detection.
method: choose between highD (default) and 2D haystack.

Value

An object of class "haystack"