binSpectMultiMatrix#
Description#
binSpect for a single spatial network and a provided expression matrix
Usage#
binSpectMultiMatrix(
expression_matrix,
spatial_networks,
bin_method = c("kmeans", "rank"),
subset_feats = NULL,
kmeans_algo = c("kmeans", "kmeans_arma", "kmeans_arma_subset"),
nstart = 3,
iter_max = 10,
extreme_nr = 50,
sample_nr = 50,
percentage_rank = c(10, 30),
do_fisher_test = TRUE,
adjust_method = "fdr",
calc_hub = FALSE,
hub_min_int = 3,
get_av_expr = TRUE,
get_high_expr = TRUE,
implementation = c("data.table", "simple", "matrix"),
group_size = "automatic",
do_parallel = TRUE,
cores = NA,
verbose = T,
knn_params = NULL,
set.seed = NULL,
summarize = c("adj.p.value", "p.value")
)
Arguments#
|
expression matrix |
|
list of spatial networks in data.table format |
|
method to binarize gene expression |
|
only select a subset of features to test |
|
kmeans algorithm to use (kmeans, kmeans_arma, kmeans_arma_subset) |
|
kmeans: nstart parameter |
|
kmeans: iter.max parameter |
|
number of top and bottom cells (see details) |
|
total number of cells to sample (see details) |
|
vector of percentages of top cells for binarization |
|
perform fisher test |
|
p-value adjusted method to use
(see |
|
calculate the number of hub cells |
|
minimum number of cell-cell interactions for a hub cell |
|
calculate the average expression per gene of the high expressing cells |
|
calculate the number of high expressing cells per gene |
|
enrichment implementation (data.table, simple, matrix) |
|
number of genes to process together with data.table implementation (default = automatic) |
|
run calculations in parallel with mclapply |
|
number of cores to use if do_parallel = TRUE |
|
be verbose |
|
list of parameters to create spatial kNN network |
|
set a seed before kmeans binarization |
|
summarize the p-values or adjusted p-values |
Value#
data.table with results