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scripts/parse_kemmeren_data.R

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+library(tidyverse)
+library(here)
+library(httr)
+library(arrow)
+library(readxl)
+
+# genomic feature harmonization table ----
+# see https://huggingface.co/datasets/BrentLab/yeast_genome_resources
+gene_table = arrow::open_dataset(here("data/genome_files/hf/features")) %>%
+  as_tibble()
+
+## there is a mislabeling in both regulator and target
+## with YDR022C. The common name is given as CIS1. However,
+## SGD reports YDR022C as ATG31. CIS1 systematic ID is YLR346C
+## That is labeled as ATG31.
+## This appears to be a swap
+
+## regulator and geneSymbol LUG1 is actually YCR087C-A, which was
+## made an alias but only documented on SGD, not actually in the
+## GFF/GTF. This needs to be updated in the gene_table as an alias
+
+add_datatype_to_colnames = function(df, skip_indicies){
+  # Suffixes to append
+  suffixes <- c("_M", "_A", "_pval")
+
+  # Repeat the suffixes to match the length of my_vector
+  repeated_suffixes <- rep(suffixes, length.out = length(colnames(df)[-skip_indicies]))
+
+  # Append the suffixes to each element of my_vector
+  modified_vector <- paste0(colnames(df)[-skip_indicies], repeated_suffixes)
+
+  colnames(df)[-skip_indicies] = modified_vector
+
+  # drop the first row, which is the "data type" row in the original data
+  # where the entries are M, A and P_value. These entries are added to the
+  # colname
+  df[-1,]
+}
+
+get_clean_headers = function(path, skip_indicies = 1:3) {
+  headers <- read_tsv(path, n_max = 1, name_repair = "minimal") %>%
+    add_datatype_to_colnames(skip_indicies = skip_indicies) %>%
+    colnames()
+
+  # Replace " vs" (optionally followed by ".") with ";"
+  headers <- str_replace(headers, " vs\\.? ", ";")
+
+  # Find empty (or NA) headers and replace with X1, X2, ...
+  empties <- which(is.na(headers) | headers == "")
+  if (length(empties) > 0) {
+    headers[empties] <- paste0("X", seq_along(empties))
+  }
+
+  headers
+}
+
+read_in_kemmeren_data = function(path, ...){
+  read.delim(path,
+             sep='\t',
+             skip=2,
+             check.names=FALSE,
+             col.names=get_clean_headers(path, ...)) %>%
+    as_tibble()
+}
+
+stopifnot(identical(get_clean_headers(here('data/kemmeren/deleteome_all_mutants_ex_wt_var_controls.txt.xz')),
+                    get_clean_headers(here('data/kemmeren/deleteome_all_mutants_controls.txt.xz'))))
+
+deleteome_all_mutants_controls =
+  read_in_kemmeren_data(here('data/kemmeren/deleteome_all_mutants_controls.txt.xz'))
+
+deleteome_ex_wt_var_controls =
+  read_in_kemmeren_data(here('data/kemmeren/deleteome_all_mutants_ex_wt_var_controls.txt.xz'))
+
+by_hand_locustag_map = tibble(
+  systematicName = c('YAR062W', 'YDL038C', 'snR10',     'YGR272C',   'YIL080W',    'YIL168W', 'YIR044C'),
+  locus_tag      = c('YAR061W', 'YDL039C', 'YNCG0013W', 'YGR271C-A', 'YIL082W-A', 'YIL167W', 'YIR043C')) %>%
+  deframe()
+
+by_hand_symbol_map = gene_table %>%
+  filter(locus_tag %in% by_hand_locustag_map) %>%
+  select(locus_tag, symbol) %>%
+  deframe()
+
+# note that by using the target_locus_tag and target_symbol,
+# the YCR087C-A,  YLR352W nomenclature is fixed (in original,
+# YCR087C-A was called LUG1, but that name was removed in 2012 per SGD.)
+# Additionally, the YDR022C/CIS1 error is corrected by using target_locus_tag
+# and target_symbol, and aligns with the deletion evidence (the TF labelled
+# ATG31/YDR022C is KOed at YDR022C, not YLR346C, which is what is
+# currently labeled CIS1)
+target_df = deleteome_all_mutants_controls %>%
+  select(reporterId, systematicName, geneSymbol) %>%
+  distinct() %>%
+  left_join(select(gene_table, locus_tag, symbol) %>%
+              mutate(systematicName = locus_tag)) %>%
+  mutate(locus_tag = ifelse(is.na(locus_tag), by_hand_locustag_map[systematicName], locus_tag)) %>%
+  mutate(symbol = ifelse(is.na(symbol), by_hand_symbol_map[locus_tag], symbol)) %>%
+  group_by(locus_tag) %>%
+  mutate(multiple_probes = n()>1) %>%
+  ungroup() %>%
+  mutate(variable_in_wt = reporterId %in%
+           setdiff(deleteome_all_mutants_controls$reporterId,
+                   deleteome_ex_wt_var_controls$reporterId)) %>%
+  dplyr::rename(target_locus_tag = locus_tag,
+                target_symbol = symbol)
+
+rm(deleteome_ex_wt_var_controls)
+gc()
+
+deleteome_all_mutants_controls_long = deleteome_all_mutants_controls %>%
+  pivot_longer(-c(reporterId, systematicName, geneSymbol),
+               names_to='sample_metric', values_to='values') %>%
+  separate(sample_metric, c('sample', 'metric'), sep="_") %>%
+  pivot_wider(names_from='metric', values_from='values') %>%
+  separate_wider_delim(cols=sample,
+                       names=c('kemmeren_regulator', 'control'),
+                       delim=";") %>%
+  mutate(kemmeren_regulator = toupper(str_remove(tolower(kemmeren_regulator), "-del-1$|-del-mata$|-del$"))) %>%
+  mutate(kemmeren_regulator = ifelse(kemmeren_regulator == "ARG5,6", "ARG56", kemmeren_regulator))
+
+kem_sup1_regulator_info = read_excel(here("data/kemmeren/mmc1.xlsx")) %>%
+  # additional columns are not tabular
+  .[,1:9]
+
+parsed_regulators = deleteome_all_mutants_controls_long %>%
+  select(kemmeren_regulator) %>%
+  distinct()
+
+regulators_munging_list = list()
+
+regulators_munging_list$x1 = parsed_regulators %>%
+  mutate(gene = kemmeren_regulator) %>%
+  left_join(kem_sup1_regulator_info) %>%
+  filter(complete.cases(.))
+
+regulators_munging_list$x2 = parsed_regulators %>%
+  filter(!kemmeren_regulator %in% regulators_munging_list$x1$kemmeren_regulator) %>%
+  mutate(`orf name` = kemmeren_regulator) %>%
+  left_join(kem_sup1_regulator_info) %>%
+  filter(complete.cases(.))
+
+stopifnot(length(intersect(regulators_munging_list$x1$kemmeren_regulator, regulators_munging_list$x2)) == 0)
+
+regulators_munging_list$x3 = read_csv(here("data/kemmeren/supplement_failure_regulator_mapping.csv.gz"))
+
+stopifnot(length(intersect(regulators_munging_list$x2$kemmeren_regulator, regulators_munging_list$x3$kemmeren_regulator)) == 0)
+
+regulators_munging_df = bind_rows(regulators_munging_list) %>%
+  # the orf name for these two was the symbol
+  mutate(`orf name` = case_when(
+    `orf name` == "TLC1" ~ "YNCB0010W",
+    `orf name` == "CMS1" ~ "YLR003C",
+    .default = `orf name`
+  )) %>%
+  filter(kemmeren_regulator != "LUG1") %>%
+  bind_rows(tibble(
+    kemmeren_regulator = "LUG1",
+    gene = "YCR087C-A",
+    `orf name` = "YCR087C-A",
+    description = paste0("Protein of unknown function; binds zinc; phosphomutants ",
+                         "exhibit phenotypes, suggesting functionality of phosphosites; green ",
+                         "fluorescent protein (GFP)-fusion protein localizes to the nucleolus; ",
+                         "YCR087C-A is not an essential gene"),
+    `functional category` = "unknown",
+    `slide(s)` = "THM_00005835_S01 / THM_00005836_S01",
+    `mating type` = "MATalpha",
+    `source of deletion mutant(s)` = "Open Biosystems / Open Biosystems",
+    `primary Hybset(s)` = "THM006 / THM006",
+    `responsive/non-responsive` = "responsive mutant",
+    chase_notes = paste0("This was originally called LUG1. However, that name ",
+                         "for this locus was removed in 2012 per SGD. The expression confirms ",
+                         "that the KO locus is YCR087C-A, not YLR352W, which is the locus ",
+                         "currently called LUG1 in 2025"))) %>%
+  left_join(
+    select(gene_table, locus_tag, symbol) %>%
+      mutate(`orf name` = locus_tag) %>%
+      dplyr::rename(regulator_locus_tag = locus_tag,
+                    regulator_symbol = symbol)) %>%
+  replace_na(list(chase_notes = "none")) %>%
+  mutate(regulator_locus_tag = ifelse(str_detect(kemmeren_regulator, "^WT-"), kemmeren_regulator, regulator_locus_tag),
+         regulator_symbol = ifelse(str_detect(kemmeren_regulator, "^WT-"), kemmeren_regulator, regulator_symbol))
+
+
+stopifnot(setequal(regulators_munging_df$kemmeren_regulator,
+                   unique(deleteome_all_mutants_controls_long$kemmeren_regulator)))
+
+deleteome_all_mutants_svd_transforms =
+  read_tsv(here("data/kemmeren/deleteome_all_mutants_svd_transformed.txt.xz"),
+           name_repair = "minimal")
+
+colnames(deleteome_all_mutants_svd_transforms)[1] = "systematicName"
+
+colnames(deleteome_all_mutants_svd_transforms) =
+  str_replace(colnames(deleteome_all_mutants_svd_transforms), "mf.alpha.1", "mf(alpha)1")
+colnames(deleteome_all_mutants_svd_transforms) =
+  str_replace(colnames(deleteome_all_mutants_svd_transforms), "mf.alpha.2", "mf(alpha)2")
+colnames(deleteome_all_mutants_svd_transforms) =
+  str_replace(colnames(deleteome_all_mutants_svd_transforms), "arg5.6", "arg56")
+
+deleteome_all_mutants_svd_transforms_long = deleteome_all_mutants_svd_transforms %>%
+  dplyr::rename(geneSymbol = commonName) %>%
+  pivot_longer(-c(systematicName, geneSymbol),
+               names_to = "condition",
+               values_to = "Madj")  %>%
+  separate_wider_delim(condition,
+                       names = c("kemmeren_regulator", "tmp"),
+                       delim = ".",
+                       too_many = "merge") %>%
+  mutate(kemmeren_regulator = toupper(kemmeren_regulator)) %>%
+  mutate(
+    # these regulators are missing appropriate suffixes
+    kemmeren_regulator = recode(kemmeren_regulator,
+                                "YIL014C" = "YIL014C-A",
+                                "YOL086W" = "YOL086W-A",
+                                "YDR034W" = "YDR034W-B",
+                                "YAL044W" = "YAL044W-A"
+    ),
+    # these targets are incorrectly labeled with symbols rather than systematic IDs
+    systematicName = recode(systematicName,
+                            "ANR2" = "YKL047W",
+                            "CMS1" = "YLR003C"
+    )
+  ) %>%
+  # this is not in the other kemmeren data
+  filter(systematicName != "Q0010")
+
+stopifnot(length(setdiff(deleteome_all_mutants_svd_transforms_long$kemmeren_regulator,
+                         regulators_munging_df$kemmeren_regulator)) == 0)
+
+stopifnot(length(setdiff(deleteome_all_mutants_svd_transforms_long$systematicName,
+                         target_df$systematicName)) == 0)
+
+final_parsed_list = list(
+    all = deleteome_all_mutants_controls_long %>%
+      select(reporterId, kemmeren_regulator, M, A, pval) %>%
+      left_join(select(target_df, reporterId, target_locus_tag,
+                       target_symbol, multiple_probes, variable_in_wt)),
+
+    slow_growth = deleteome_all_mutants_svd_transforms_long %>%
+      select(kemmeren_regulator, systematicName, Madj) %>%
+      # necessary to wrap in distinct to eliminate cases where there are two reporterId
+      left_join(distinct(select(target_df, systematicName, target_locus_tag, target_symbol))) %>%
+      select(-systematicName)
+)
+
+final_parsed_df = Reduce(left_join, final_parsed_list) %>%
+  group_by(kemmeren_regulator) %>%
+  # since the slow growth removed data identifies records by systematicName
+  # and not reporterId, there is a many-to-many join and one reporterId is
+  # duplicated to mulitple Madj. This removes those duplicates
+  distinct(reporterId, .keep_all = TRUE) %>%
+  ungroup() %>%
+  left_join(select(regulators_munging_df, kemmeren_regulator,
+                   regulator_locus_tag, regulator_symbol)) %>%
+  select(regulator_locus_tag, regulator_symbol, reporterId,
+         target_locus_tag, target_symbol, M, Madj, A, pval,
+         variable_in_wt, multiple_probes)
+
+final_parsed_df %>%
+  arrange(regulator_locus_tag) %>%
+  write_parquet(here("data/kemmeren/kemmeren_2014.parquet"),
+                compression = "zstd",
+                chunk_size = 6181,
+                write_statistics = TRUE,
+                use_dictionary = c(
+                  regulator_locus_tag = TRUE,
+                  target_locus_tag = TRUE
+                )
+  )