## ---- eval = FALSE--------------------------------------------------------- # install.packages("BiocManager") # BiocManager::install("anamiR") ## -------------------------------------------------------------------------- library(anamiR) ## -------------------------------------------------------------------------- data(mrna) data(mirna) data(pheno.mirna) data(pheno.mrna) ## -------------------------------------------------------------------------- mrna[1:5, 1:5] ## -------------------------------------------------------------------------- mirna[1:5, 1:5] ## -------------------------------------------------------------------------- pheno.mrna[1:3, 1:3] pheno.mrna[28:30, 1:3] ## ---- eval = FALSE--------------------------------------------------------- # se <- normalization(data = mirna, method = "quantile") ## -------------------------------------------------------------------------- mrna_se <- SummarizedExperiment::SummarizedExperiment( assays = S4Vectors::SimpleList(counts=mrna), colData = pheno.mrna) mirna_se <- SummarizedExperiment::SummarizedExperiment( assays = S4Vectors::SimpleList(counts=mirna), colData = pheno.mirna) ## -------------------------------------------------------------------------- mrna_d <- differExp_discrete(se = mrna_se, class = "ER", method = "t.test", t_test.var = FALSE, log2 = FALSE, p_value.cutoff = 0.05, logratio = 0.5 ) mirna_d <- differExp_discrete(se = mirna_se, class = "ER", method = "t.test", t_test.var = FALSE, log2 = FALSE, p_value.cutoff = 0.05, logratio = 0.5 ) ## -------------------------------------------------------------------------- nc <- ncol(mrna_d) mrna_d[1:5, (nc-4):nc] ## -------------------------------------------------------------------------- mirna_21 <- miR_converter(data = mirna_d, remove_old = TRUE, original_version = 17, latest_version = 21) ## -------------------------------------------------------------------------- # Before head(row.names(mirna_d)) # After head(row.names(mirna_21)) ## -------------------------------------------------------------------------- cor <- negative_cor(mrna_data = mrna_d, mirna_data = mirna_21, method = "pearson", cut.off = -0.5) ## -------------------------------------------------------------------------- head(cor) ## -------------------------------------------------------------------------- heat_vis(cor, mrna_d, mirna_21) ## -------------------------------------------------------------------------- sup <- database_support(cor_data = cor, org = "hsa", Sum.cutoff = 3) ## -------------------------------------------------------------------------- head(sup) ## -------------------------------------------------------------------------- path <- enrichment(data_support = sup, org = "hsa", per_time = 500) ## -------------------------------------------------------------------------- head(path) ## -------------------------------------------------------------------------- require(data.table) aa <- system.file("extdata", "GSE19536_mrna.csv", package = "anamiR") mrna <- fread(aa, fill = TRUE, header = TRUE) bb <- system.file("extdata", "GSE19536_mirna.csv", package = "anamiR") mirna <- fread(bb, fill = TRUE, header = TRUE) cc <- system.file("extdata", "pheno_data.csv", package = "anamiR") pheno.data <- fread(cc, fill = TRUE, header = TRUE) ## -------------------------------------------------------------------------- mirna_name <- mirna[["miRNA"]] mrna_name <- mrna[["Gene"]] mirna <- mirna[, -1] mrna <- mrna[, -1] mirna <- data.matrix(mirna) mrna <- data.matrix(mrna) row.names(mirna) <- mirna_name row.names(mrna) <- mrna_name pheno_name <- pheno.data[["Sample"]] pheno.data <- pheno.data[, -1] pheno.data <- as.matrix(pheno.data) row.names(pheno.data) <- pheno_name ## -------------------------------------------------------------------------- mrna[1:5, 1:5] ## -------------------------------------------------------------------------- mirna[1:5, 1:5] ## -------------------------------------------------------------------------- pheno.data[1:5, 1] pheno.data[94:98, 1] ## -------------------------------------------------------------------------- mrna_se <- SummarizedExperiment::SummarizedExperiment( assays = S4Vectors::SimpleList(counts=mrna), colData = pheno.data) mirna_se <- SummarizedExperiment::SummarizedExperiment( assays = S4Vectors::SimpleList(counts=mirna), colData = pheno.data) ## ---- eval = FALSE--------------------------------------------------------- # table <- GSEA_ana(mrna_se = mrna_se, mirna_se = mirna_se, class = "ER", pathway_num = 2) ## -------------------------------------------------------------------------- data(table_pre) ## -------------------------------------------------------------------------- names(table_pre)[1] table_pre[[1]][1:5, 1:5] names(table_pre)[2] table_pre[[2]][1:5, 1:5] ## -------------------------------------------------------------------------- result <- GSEA_res(table = table_pre, pheno.data = pheno.data, class = "ER", DE_method = "limma", cor_cut = 0) ## -------------------------------------------------------------------------- names(result)[1] result[[1]]