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scripts/parse_barkai_checseq.R

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+## NOTE: The data is currently on /lts/mblab/downloaded_data/barkai_checseq
+## and the parquet dataset is on the brentlab-strides aws at s3://yeast-binding-perturbation-data/barkai_checkseq
+
+library(tidyverse)
+library(here)
+library(arrow)
+
+sacCer3_genome = rtracklayer::import("~/ref/sacCer3/ucsc/sacCer3.fa.gz", format="fasta")
+
+sacCer3_seqnames = unlist(map(str_split(names(sacCer3_genome), " "), ~.[[1]]))
+
+sacCer3_genome_df = tibble(
+  seqnames = rep(sacCer3_seqnames, Biostrings::width(sacCer3_genome))
+) %>%
+  group_by(seqnames) %>%
+  mutate(start = row_number()-1,
+         end = row_number()) %>%
+  ungroup()
+
+retrieve_series_paths = function(series_id){
+  sra_meta_path = file.path("data/barkai_checseq", series_id, "SraRunTable.csv")
+  stopifnot(file.exists(sra_meta_path))
+  df = read_csv(sra_meta_path)
+
+  data_files = list.files(here("data/barkai_checseq", series_id), "*.txt.gz", full.names = TRUE)
+
+  stopifnot(nrow(df) == length(data_files))
+
+  names(data_files) = str_extract(basename(data_files), "GSM\\d+")
+
+  list(
+    meta = sra_meta_path,
+    files = data_files
+  )
+}
+
+
+add_genomic_coordinate = function(checseqpath){
+
+  bind_cols(sacCer3_genome_df,
+            data.table::fread(checseqpath, sep = "\t", col.names='pileup'))
+
+}
+
+process_checseq_files = function(file){
+
+  add_genomic_coordinate(file) %>%
+    filter(pileup != 0)
+}
+
+series_list = map(set_names(c("GSE179430", "GSE209631", "GSE222268")), retrieve_series_paths)
+
+dataset_basepath = here("data/barkai_checseq/hf/genome_map")
+
+# Create output directory
+dir.create(dataset_basepath, recursive = TRUE, showWarnings = FALSE)
+
+for (series_id in names(series_list)) {
+
+  message(glue::glue("Processing series {series_id}"))
+
+  for (accession_id in names(series_list[[series_id]]$files)) {
+
+    message(glue::glue("  Processing {accession_id}"))
+
+    df <- process_checseq_files(
+      series_list[[series_id]]$files[[accession_id]]
+    ) %>%
+      mutate(accession = accession_id, series = series_id)
+
+    df %>%
+      group_by(seqnames) %>%
+    write_dataset(
+      path = dataset_basepath,
+      format = "parquet",
+      partitioning = c("series", "accession"),
+      existing_data_behavior = "overwrite",
+      compression = "zstd",
+      write_statistics = TRUE,
+      use_dictionary = c(
+        seqnames = TRUE
+      )
+    )
+
+    gc()
+  }
+}
+
+# the following code was used to parse an entire series to DF and then save
+# to a parquet dataset. that was too large and I chose the dataset partitioning
+# instead.
+
+# split_manipulation <- function(manipulation_str) {
+#   parts <- str_split(manipulation_str, "::")[[1]]
+#
+#   if (length(parts) != 2) {
+#     stop("Unexpected format. Expected 'LOCUS::TAGGED_CONSTRUCT'")
+#   }
+#
+#   tagged_locus <- parts[1]
+#   rhs <- parts[2]
+#
+#   # default
+#   dbd_donor_symbol_str <- "none"
+#   ortholog <- "none"
+#
+#   # Check for paralog DBD
+#   if (str_detect(rhs, "-[A-Za-z0-9]+DBD-Mnase$")) {
+#     dbd_donor_symbol_str <- toupper(str_remove(str_split(rhs, "-", simplify = TRUE)[[2]], "DBD"))
+#   } else if (str_detect(rhs, "^K\\.lactis .*?-Mnase$")) {
+#     ortholog <- rhs
+#   }
+#
+#   list(
+#     mnase_tagged_symbol = tagged_locus,
+#     dbd_donor_symbol = dbd_donor_symbol_str,
+#     ortholog_donor = ortholog
+#   )
+# }
+#
+#
+# split_deletion <- function(deletion_str) {
+#   parts <- str_split(deletion_str, "::", simplify = TRUE)
+#
+#   list(
+#     paralog_deletion_symbol = parts[1],
+#     paralog_resistance_cassette = if (ncol(parts) >= 2) parts[2] else "none"
+#   )
+# }
+#
+# split_construct_to_tibble = function(split_list){
+#   background = list(background=split_list[[1]])
+#   manipulation_list = split_manipulation(split_list[[2]])
+#   deletion_list = split_deletion(tryCatch(split_list[[3]], error = function(e) "none"))
+#
+#   bind_cols(map(list(background, manipulation_list, deletion_list), as_tibble))
+#
+# }
+#
+#
+# split_constructs <- function(s) {
+#   s <- str_trim(s)
+#   if (s == "" || is.na(s)) return(character(0))
+#   # split on spaces ONLY when the next token starts a new locus "XYZ::"
+#   split_geno = str_split(s, "\\s+(?=[A-Za-z0-9_.()\\-]+::)")[[1]]
+#
+#   bind_cols(tibble(genotype = s), split_construct_to_tibble(split_geno))
+#
+#
+# }
+#
+# gse178430_parsed_meta = bind_cols(
+#   select(gse178430_meta, `GEO_Accession (exp)`, strainid, Instrument) %>%
+#     dplyr::rename(accession = `GEO_Accession (exp)`,
+#                   instrument = Instrument),
+#   bind_rows(map(gse178430_meta$genotype, split_constructs))
+# )