Delete scripts

scripts

@@ -1,157 +0,0 @@
-## 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))
-# )