SpicyResults-class {spicyR} | R Documentation |
Performs spatial tests on spatial cytometry data.
spicy( cells, condition = NULL, subject = NULL, covariates = NULL, from = NULL, to = NULL, dist = NULL, integrate = TRUE, nsim = NULL, verbose = TRUE, weights = TRUE, weightsByPair = FALSE, weightFactor = 1, window = "convex", window.length = NULL, BPPARAM = BiocParallel::SerialParam(), sigma = NULL, Rs = NULL, minLambda = 0.05, fast = TRUE, edgeCorrect = TRUE, ... )
cells |
A SegmentedCells or data frame that contains at least the variables x and y, giving the location coordinates of each cell, and cellType. |
condition |
Vector of conditions to be tested corresponding to each image if cells is a data frame. |
subject |
Vector of subject IDs corresponding to each image if cells is a data frame. |
covariates |
Vector of covariate names that should be included in the mixed effects model as fixed effects. |
from |
vector of cell types which you would like to compare to the to vector |
to |
vector of cell types which you would like to compare to the from vector |
dist |
The distance at which the statistic is obtained. |
integrate |
Should the statistic be the integral from 0 to dist, or the value of the L curve at dist. |
nsim |
Number of simulations to perform. If empty, the p-value from lmerTest is used. |
verbose |
logical indicating whether to output messages. |
weights |
logical indicating whether to include weights based on cell counts. |
weightsByPair |
logical indicating whether weights should be calculated for each cell type pair. |
weightFactor |
numeric that controls the convexity of the weight function. |
window |
Should the window around the regions be 'square', 'convex' or 'concave'. |
window.length |
A tuning parameter for controlling the level of concavity when estimating concave windows. |
BPPARAM |
A BiocParallelParam object. |
sigma |
A numeric variable used for scaling when fitting inhomogeneous L-curves. |
Rs |
A vector of the radii that the measures of association should be calculated. |
minLambda |
Minimum value for density for scaling when fitting inhomogeneous L-curves. |
fast |
A logical describing whether to use a fast approximation of the inhomogeneous L-curves. |
edgeCorrect |
A logical indicating whether to perform edge correction. |
... |
Other options to pass to bootstrap. |
Data frame of p-values.
data("diabetesData") # Test with random effect for patient on only one pairwise combination of cell types. spicy(diabetesData, condition = "stage", subject = "case", from = "Tc", to = "Th") # Test all pairwise combination of cell types without random effect of patient. #spicyTest <- spicy(diabetesData, condition = "stage", subject = "case") # Test all pairwise combination of cell types with random effect of patient. #spicy(diabetesData, condition = "condition", subject = "subject") # Test all pairwise combination of cell types with random effect of patient using # a bootstrap to calculate significance. #spicy(diabetesData, condition = "stage", subject = "case", nsim = 10000)