# Find clusters containing core substrates `clust.expand` returns a list of kinase substrate relationships ```r clust.expand(clust, clust_all, diff = NULL) ``` ## Arguments - `clust`: named list containing named vectors of cluster assignments, names correspond to rownames in data and names of list are kinase identifiers (result of clustering performed using exclusive substrates) - `clust_all`: named list containing named vectors of cluster assignments, names correspond to rownames in data and names of list are kinase identifiers (result of clustering performed using all substrates) - `diff`: character vector of substrate identifiers that are differentially regulated ## Returns named list containing named vectors of cluster assignments, names correspond to rownames in data and names of list are kinase identifiers ## Details The function clust.expand takes the resulting core substrates from the exclusive clustering and finds the corresponding substrate clusters in the clustering using all substrates. ## Examples ```r data(phosphonetworkdf) data(datakin) # only need what is present in data phosphonetwork_data <- phosphonetwork_df[ phosphonetwork_df[,"SUB_IDENT"] %in% data_kin[,"SUB_IDENT"] ,] fam <- list(akt = c("P31749", "P31751")) kin_data_fam_exc <- KSR.list(phosphonetwork_data[, c("SUB_IDENT", "KIN_ACC_ID")], kinasefamilies = fam, exclusive = TRUE) # only do for Akt and Mtor (P31749, P42345) substrate_profiles <- lapply(kin_data_fam_exc[c("P31749", "P42345")], function(x){data_kin[match(x, data_kin[,"SUB_IDENT"]),1:9]}) substrate_profiles_random <- lapply(substrate_profiles, function(x){rbind(x, random.data(x, random.seed = 123))}) target <- 3 substrate_profiles_tight <- lapply(substrate_profiles_random, function(x){ tightClust::tight.clust(x, target = target, k.min = 7, resamp.num = 100, random.seed = 12345) }) kin_clust<- mapply(function(x,y){clustering(x, y)}, substrate_profiles_tight, substrate_profiles, SIMPLIFY = FALSE) # do clustering using all available substrates kin_data_fam <- KSR.list(phosphonetwork_data[, c("SUB_IDENT", "KIN_ACC_ID")], kinasefamilies = fam) substrate_profiles_all <- lapply(kin_data_fam[c("P31749", "P42345")], function(x){data_kin[match(x, data_kin[,"SUB_IDENT"]),1:9]}) substrate_profiles_random_all <- lapply(substrate_profiles_all, function(x){rbind(x, random.data(x, random.seed = 123))}) target <- 3 substrate_profiles_tight_all <- lapply(substrate_profiles_random_all, function(x){ tightClust::tight.clust(x, target = target, k.min = 7, resamp.num = 100, random.seed = 12345) }) kin_clust_all <- mapply(function(x,y){clustering(x, y)}, substrate_profiles_tight_all, substrate_profiles_all, SIMPLIFY = FALSE) expand_all <- mapply(function(x,y){clust.expand(x, y)}, kin_clust, kin_clust_all, SIMPLIFY = FALSE) ```

clust.expand function