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| #!/usr/bin/env Rscript | |
| # Export the controlled HarmanData microarray studies to BE_leaderboard's | |
| # name/batch/label/numeric-features CSV contract. | |
| args <- commandArgs(trailingOnly = TRUE) | |
| repo_root <- if (length(args) >= 1) normalizePath(args[[1]], mustWork = TRUE) else getwd() | |
| if (!requireNamespace("HarmanData", quietly = TRUE)) { | |
| stop("HarmanData is required. Install it with BiocManager::install('HarmanData').") | |
| } | |
| export_study <- function(bundle_name, data_name, info_name, dataset_id, label_column, max_features = 2048) { | |
| data(list = bundle_name, package = "HarmanData", envir = environment()) | |
| feature_matrix <- get(data_name, envir = environment()) | |
| sample_info <- get(info_name, envir = environment()) | |
| if (ncol(feature_matrix) != nrow(sample_info)) { | |
| stop(sprintf("%s feature/sample dimensions do not match metadata", dataset_id)) | |
| } | |
| if (!all(c(label_column, "Batch") %in% colnames(sample_info))) { | |
| stop(sprintf("%s metadata lacks %s or Batch", dataset_id, label_column)) | |
| } | |
| sample_names <- colnames(feature_matrix) | |
| info_names <- rownames(sample_info) | |
| if (!is.null(sample_names) && !is.null(info_names)) { | |
| positions <- match(sample_names, info_names) | |
| if (anyNA(positions)) stop(sprintf("%s sample names do not match metadata", dataset_id)) | |
| sample_info <- sample_info[positions, , drop = FALSE] | |
| } | |
| if (is.null(sample_names)) sample_names <- info_names | |
| variances <- apply(feature_matrix, 1, var, na.rm = TRUE) | |
| variances[!is.finite(variances)] <- -Inf | |
| keep <- order(variances, decreasing = TRUE)[seq_len(min(max_features, nrow(feature_matrix)))] | |
| feature_matrix <- feature_matrix[keep, , drop = FALSE] | |
| rownames(feature_matrix) <- make.unique(rownames(feature_matrix)) | |
| features <- as.data.frame(t(feature_matrix), check.names = FALSE) | |
| output <- data.frame( | |
| name = as.character(sample_names), | |
| batch = paste0("batch_", as.character(sample_info[["Batch"]])), | |
| label = as.character(sample_info[[label_column]]), | |
| features, | |
| check.names = FALSE | |
| ) | |
| if (anyNA(output[, c("name", "batch", "label")])) { | |
| stop(sprintf("%s contains missing required metadata", dataset_id)) | |
| } | |
| target_dir <- file.path(repo_root, "data", "datasets", dataset_id) | |
| dir.create(target_dir, recursive = TRUE, showWarnings = FALSE) | |
| target <- file.path(target_dir, paste0(dataset_id, "_train.csv")) | |
| write.csv(output, target, row.names = FALSE, quote = TRUE) | |
| message(sprintf("wrote %s (%d samples, %d top-variance features)", target, nrow(features), ncol(features))) | |
| } | |
| export_study("NPM", "npm.data", "npm.info", "harman_npm", "Treatment") | |
| export_study("OLF", "olf.data", "olf.info", "harman_olf", "Treatment") | |