View source: R/haystack_highD.R
haystack_highD | R Documentation |
The main Haystack function, for higher-dimensional spaces.
haystack_highD( x, detection, grid.points = 100, use.advanced.sampling = NULL, dir.randomization = NULL, scale = TRUE, grid.method = "centroid" )
x |
Coordinates of cells in a 2D or higher-dimensional space. Rows represent cells, columns the dimensions of the space. |
detection |
A logical matrix showing which genes (rows) are detected in which 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. |
use.advanced.sampling |
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.method |
The method to decide grid points for estimating the density in the high-dimensional space. Should be "centroid" (default) or "seeding". |
An object of class "haystack", including the results of the analysis, and the coordinates of the grid points used to estimate densities.
# I need to add some examples. # A toy example will be added too.
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