haystack_continuous_highD: The main Haystack function, for higher-dimensional spaces and...

In singleCellHaystack: A Universal Differential Expression Prediction Tool for Single-Cell and Spatial Genomics Data

The main Haystack function, for higher-dimensional spaces and continuous expression levels.

Description

The main Haystack function, for higher-dimensional spaces and continuous expression levels.

Usage

haystack_continuous_highD(
  x,
  expression,
  grid.points = 100,
  weights.advanced.Q = NULL,
  dir.randomization = NULL,
  scale = TRUE,
  grid.method = "centroid",
  randomization.count = 100,
  n.genes.to.randomize = 100,
  selection.method.genes.to.randomize = "heavytails",
  grid.coord = NULL,
  spline.method = "ns"
)

Arguments

x	Coordinates of cells in a 2D or higher-dimensional space. Rows represent cells, columns the dimensions of the space.
expression	a matrix with expression data of genes (rows) in cells (columns)
grid.points	An integer specifying the number of centers (grid points) to be used for estimating the density distributions of cells. Default is set to 100.
weights.advanced.Q	(Default: NULL) Optional weights of cells for calculating a weighted distribution of expression.
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.method	The method to decide grid points for estimating the density in the high-dimensional space. Should be "centroid" (default) or "seeding".
randomization.count	Number of randomizations to use. Default: 100
n.genes.to.randomize	Number of genes to use in randomizations. Default: 100
selection.method.genes.to.randomize	Method used to select genes for randomization.
grid.coord	matrix of grid coordinates.
spline.method	Method to use for fitting splines "ns" (default): natural splines, "bs": B-splines.

Value

An object of class "haystack", including the results of the analysis, and the coordinates of the grid points used to estimate densities.

Examples

# using the toy example of the singleCellHaystack package

# running haystack
res <- haystack(dat.tsne, dat.expression)
# list top 10 biased genes
show_result_haystack(res, n=10)

singleCellHaystack documentation built on Dec. 28, 2022, 1:29 a.m.