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pull_gse65682.R

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+# Version info: R 4.2.2, Biobase 2.58.0, GEOquery 2.66.0, limma 3.54.0
+################################################################
+#   Data plots for selected GEO samples
+library(GEOquery)
+library(limma)
+library(hgu219.db)
+library(umap)
+library(here)
+library(tidyverse)
+
+# load series and platform data from GEO
+
+dir.create("data/gse65682")
+gset <- getGEO("GSE65682", destdir = "data/gse65682", GSEMatrix = TRUE, getGPL = FALSE)
+if (length(gset) > 1) idx <- grep("GPL13667", attr(gset, "names")) else idx <- 1
+gset <- gset[[idx]]
+
+ex <- exprs(gset)
+# log2 transform
+qx <- as.numeric(quantile(ex, c(0., 0.25, 0.5, 0.75, 0.99, 1.0), na.rm = T))
+LogC <- (qx[5] > 100) ||
+    (qx[6] - qx[1] > 50 && qx[2] > 0)
+if (LogC) {
+    ex[which(ex <= 0)] <- NaN
+    ex <- log2(ex)
+}
+
+# box-and-whisker plot
+dev.new(width = 3 + ncol(gset) / 6, height = 5)
+par(mar = c(7, 4, 2, 1))
+title <- paste("GSE65682", "/", annotation(gset), sep = "")
+boxplot(ex, boxwex = 0.7, notch = T, main = title, outline = FALSE, las = 2)
+dev.off()
+
+# expression value distribution plot
+par(mar = c(4, 4, 2, 1))
+title <- paste("GSE65682", "/", annotation(gset), " value distribution", sep = "")
+plotDensities(ex, main = title, legend = F)
+
+# mean-variance trend
+ex <- na.omit(ex) # eliminate rows with NAs
+plotSA(lmFit(ex), main = "Mean variance trend, GSE65682")
+
+# UMAP plot (multi-dimensional scaling)
+ex <- ex[!duplicated(ex), ] # remove duplicates
+ump <- umap(t(ex), n_neighbors = 15, random_state = 123)
+plot(ump$layout, main = "UMAP plot, nbrs=15", xlab = "", ylab = "", pch = 20, cex = 1.5)
+
+clean_char <- function(x, prefix_regex) {
+    val <- str_squish(str_remove(x, prefix_regex))
+    na_if(val, "NA")
+}
+
+pdat_mars <- as_tibble(pData(gset), rownames = "sample_id") |>
+    select(sample_id, starts_with("characteristics"))
+
+purrr::imap(pdat_mars |> select(-sample_id), ~ count(tibble(value = .x), value, name = "n") |> arrange(desc(n)))
+
+gse65682_metadata <- as_tibble(pData(gset), rownames = "sample_id") |>
+    mutate(
+        healthy_control                = str_detect(title, "healthy"),
+        title_date                     = str_extract(title, "\\d\\d_\\d{2}_\\d{4}"),
+        title_identifier1              = str_extract(title, "(?<=\\d{2}_\\d{2}_\\d{4}_)\\w\\d+"),
+        title_identifier2              = str_extract(title, "\\d+(?=\\])"),
+        sex                            = clean_char(characteristics_ch1, "^gender:\\s*"),
+        age                            = as.numeric(clean_char(characteristics_ch1.1, "^age:\\s*")),
+        pneumonia_diagnosis            = clean_char(characteristics_ch1.2, "^pneumonia diagnoses:\\s*"),
+        thrombocytopenia               = clean_char(characteristics_ch1.3, "^thrombocytopenia:\\s*"),
+        endotype_cohort                = clean_char(characteristics_ch1.4, "^endotype_cohort:\\s*"),
+        endotype_class                 = clean_char(characteristics_ch1.5, "^endotype_class:\\s*"),
+        mortality_28d                  = as.logical(as.integer(clean_char(characteristics_ch1.6, "^mortality_event_28days:\\s*"))),
+        time_to_event_28d              = as.numeric(clean_char(characteristics_ch1.7, "^time_to_event_28days:\\s*")),
+        icu_acquired_infection         = clean_char(characteristics_ch1.8, "^icu_acquired_infection:\\s*"),
+        icu_acquired_infection_paired  = clean_char(characteristics_ch1.9, "^icu_acquired_infection_paired:\\s*"),
+        diabetes_mellitus              = clean_char(characteristics_ch1.10, "^diabetes_mellitus:\\s*"),
+        abdominal_sepsis_or_control    = clean_char(characteristics_ch1.11, "^abdominal_sepsis_and_controls:\\s*")
+    ) |>
+    dplyr::select(
+        sample_id, title_identifier1, title_identifier2, healthy_control, sex,
+        age, pneumonia_diagnosis, thrombocytopenia, endotype_cohort, endotype_class,
+        mortality_28d, time_to_event_28d, icu_acquired_infection, icu_acquired_infection_paired,
+        diabetes_mellitus, abdominal_sepsis_or_control
+    )
+
+stopifnot(gse65682_metadata |> filter(!is.na(endotype_class)) |> count(is.na(mortality_28d)) |> pull(n) == 479)
+
+your_probes_mars <- rownames(exprs(gset))
+biocu219_probes <- keys(hgu219.db, keytype = "PROBEID")
+
+length(your_probes_mars)
+length(biocu219_probes)
+length(intersect(your_probes_mars, biocu219_probes))
+stopifnot(mean(!your_probes_mars %in% biocu219_probes) == 0)
+
+anno_u219 <- AnnotationDbi::select(
+    hgu219.db,
+    keys = your_probes_mars,
+    columns = c("SYMBOL", "ENTREZID", "ENSEMBL", "GENENAME", "UNIPROT"),
+    keytype = "PROBEID"
+)
+
+gse65682_feature_metadata <- anno_u219 |>
+    group_by(PROBEID) |>
+    reframe(
+        ENSEMBL = paste(unique(na.omit(ENSEMBL)), collapse = ";"),
+        ENTREZID = dplyr::first(ENTREZID),
+        SYMBOL = dplyr::first(SYMBOL),
+        GENENAME = dplyr::first(GENENAME),
+        UNIPROT = paste(unique(na.omit(UNIPROT)), collapse = ";")
+    ) |>
+    ungroup() |>
+    mutate(across(c(ENSEMBL, UNIPROT), ~ na_if(.x, ""))) |>
+    rename(feature_id = PROBEID) |>
+    right_join(tibble(feature_id = your_probes_mars), by = "PROBEID") # guarantee every probe gets a row
+
+stopifnot(nrow(gse65682_feature_metadata) == length(your_probes_mars))
+stopifnot(!any(duplicated(gse65682_feature_metadata$feature_id)))
+
+mean(is.na(gse65682_feature_metadata$SYMBOL)) # for comparison against the other datasets' rates
+
+gse65682_expr_long <- as_tibble(exprs(gset), rownames = "feature_id") |>
+    pivot_longer(-feature_id, names_to = "sample_id", values_to = "value") |>
+    arrange(sample_id, feature_id)
+
+stopifnot(nrow(gse65682_expr_long) == nrow(exprs(gset)) * ncol(exprs(gset)))
+stopifnot(all(unique(gse65682_expr_long$sample_id) %in% gse65682_metadata$sample_id))
+stopifnot(all(unique(gse65682_expr_long$PROBEID) %in% gse65682_feature_metadata$PROBEID))
+
+stopifnot(!any(duplicated(gse65682_metadata$sample_id)))
+stopifnot(nrow(gse65682_metadata) == 802)
+
+dir.create("data/gse65682/parquet", recursive = TRUE, showWarnings = FALSE)
+
+arrow::write_parquet(gse65682_metadata, "data/gse65682/parquet/sample_metadata.parquet")
+arrow::write_parquet(gse65682_feature_metadata, "data/gse65682/parquet/feature_metadata.parquet")
+arrow::write_parquet(gse65682_expr_long, "data/gse65682/parquet/expression.parquet")