binSpectMultiMatrixΒΆ
binSpectMultiMatrix
binSpect for a single spatial network and a provided expression matrix
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") )
Argument
Description
expression_matrixexpression matrix
spatial_networkslist of spatial networks in data.table format
bin_methodmethod to binarize gene expression
subset_featsonly select a subset of features to test
kmeans_algokmeans algorithm to use (kmeans, kmeans_arma, kmeans_arma_subset)
nstartkmeans: nstart parameter
iter_maxkmeans: iter.max parameter
extreme_nrnumber of top and bottom cells (see details)
sample_nrtotal number of cells to sample (see details)
percentage_rankvector of percentages of top cells for binarization
do_fisher_testperform fisher test
adjust_methodp-value adjusted method to use (see ``p.adjust` <#p.adjust>`_ )
calc_hubcalculate the number of hub cells
hub_min_intminimum number of cell-cell interactions for a hub cell
get_av_exprcalculate the average expression per gene of the high expressing cells
get_high_exprcalculate the number of high expressing cells per gene
implementationenrichment implementation (data.table, simple, matrix)
group_sizenumber of genes to process together with data.table implementation (default = automatic)
do_parallelrun calculations in parallel with mclapply
coresnumber of cores to use if do_parallel = TRUE
verbosebe verbose
knn_paramslist of parameters to create spatial kNN network
set.seedset a seed before kmeans binarization
summarizesummarize the p-values or adjusted p-values
data.table with results