merge-lbm-seq.R

@@ -6,7 +6,7 @@ path <- args[1]
 
 
 
-base_folder <- str_remove(string = path, pattern = "/tmp[0-9]*/?$")
+base_folder <- str_remove(string = path, pattern = "/tmp[0-9]*$")
 print(base_folder)
 epoch <- str_extract(string = path, pattern = "(?<=tmp)([0-9]*)")
 

multipartite_taxtable.R

@@ -1,42 +0,0 @@
-library(sbm)
-library(phyloseq)
-library(biomformat)
-library(here)
-source("utils.R")
-
-options(parallelly.availableCores.custom = function() {
-    ncores <- min(parallelly::availableCores(), 64)
-    max(1L, ncores)
-})
-
-message(paste("Number of cores available:", parallelly::availableCores()))
-args <- commandArgs(trailingOnly = TRUE)
-if (length(args) == 0) {
-    author <- "mach"
-} else {
-    author <- args[1]
-}
-
-message("For author: ", author)
-the_data <- import_biom(here("data", author, paste0(author, ".biom")))
-
-epoch <- as.integer(Sys.time())
-
-per_taxa_networks <- collapse_otu_at_taxo(the_data)
-per_taxa_networks <- per_taxa_networks[-1]
-
-lbm_list <- lapply(seq_along(per_taxa_networks), function(idx) {
-    defineSBM(per_taxa_networks[[idx]], model = "poisson", dimLabels = c(row = paste0("Rank", idx + 1), col = "Sample"))
-})
-
-lbm_list_covariates <- lapply(seq_along(per_taxa_networks), function(idx) {
-    covar_sd <- log(rep(1, nrow(per_taxa_networks[[idx]])) %*% t(colSums(per_taxa_networks[[idx]])))
-    defineSBM(per_taxa_networks[[idx]], model = "poisson", dimLabels = c(row = paste0("Rank", idx + 1), col = "Sample"), covariates = list(covar_sd))
-})
-
-
-multipartite_fit <- estimateMultipartiteSBM(listSBM = lbm_list, estimOptions = list(initBM = FALSE))
-
-multipartite_covariates_fit <- estimateMultipartiteSBM(listSBM = lbm_list_covariates, estimOptions = list(initBM = FALSE))
-
-plot(multipartite_covariates_fit)