File size: 13,156 Bytes
549f84e 605a7db 549f84e 605a7db 549f84e 605a7db 549f84e 27d8764 549f84e 27d8764 605a7db 27d8764 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 |
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$"))) %>%
mutate(kemmeren_regulator = ifelse(kemmeren_regulator == "ARG5,6", "ARG56", kemmeren_regulator))
kem_sup1_regulator_info = read_excel(here("data/kemmeren/supplemental_table1_strain_info.xlsx")) %>%
mutate(`profile first published` = str_replace(`profile first published`, ", ", ","))
kem_sup1_regulator_info_straininfo = read_excel(here("data/kemmeren/supplemental_table1_strain_info_origins.xlsx"))
kem_sup1_regulator_info = kem_sup1_regulator_info %>%
left_join(kem_sup1_regulator_info_straininfo) %>%
mutate(`profile first published` = citation) %>%
select(-citation)
parsed_regulators = deleteome_all_mutants_controls_long %>%
select(kemmeren_regulator) %>%
distinct()
regulators_munging_list = list()
regulators_munging_list$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$kemmeren_regulator)) == 0)
regulators_munging_df = bind_rows(regulators_munging_list) %>%
# the orf name for these two was the symbol
mutate(`orf name` = case_when(
`orf name` == "TLC1" ~ "YNCB0010W",
`orf name` == "CMS1" ~ "YLR003C",
.default = `orf name`
)) %>%
filter(kemmeren_regulator != "LUG1") %>%
bind_rows(tibble(
kemmeren_regulator = "LUG1",
gene = "YCR087C-A",
`orf name` = "YCR087C-A",
description = paste0("Protein of unknown function; binds zinc; phosphomutants ",
"exhibit phenotypes, suggesting functionality of phosphosites; green ",
"fluorescent protein (GFP)-fusion protein localizes to the nucleolus; ",
"YCR087C-A is not an essential gene"),
`functional category` = "unknown",
`slide(s)` = "THM_00005835_S01 / THM_00005836_S01",
`mating type` = "MATalpha",
`source of deletion mutant(s)` = "Open Biosystems / Open Biosystems",
`primary Hybset(s)` = "THM006 / THM006",
`responsive/non-responsive` = "responsive mutant",
chase_notes = paste0("This was originally called LUG1. However, that name ",
"for this locus was removed in 2012 per SGD. The expression confirms ",
"that the KO locus is YCR087C-A, not YLR352W, which is the locus ",
"currently called LUG1 in 2025"))) %>%
left_join(
select(gene_table, locus_tag, symbol) %>%
mutate(`orf name` = locus_tag) %>%
dplyr::rename(regulator_locus_tag = locus_tag,
regulator_symbol = symbol)) %>%
replace_na(list(chase_notes = "none")) %>%
mutate(regulator_locus_tag = ifelse(str_detect(kemmeren_regulator, "^WT-"), kemmeren_regulator, regulator_locus_tag),
regulator_symbol = ifelse(str_detect(kemmeren_regulator, "^WT-"), kemmeren_regulator, regulator_symbol)) %>%
janitor::clean_names()
stopifnot(setequal(regulators_munging_df$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,
-c(gene, `orf_name`))) %>%
dplyr::rename(nr_sign_changes = nr_sign_changes_p_0_05_fc_1_7,
primary_hybsets = primary_hybset_s,
source_of_deletion_mutants = source_of_deletion_mutant_s,
slides = slide_s,
regulator_desc = description) %>%
arrange(regulator_locus_tag)
# select(regulator_locus_tag, regulator_symbol, reporterId,
# target_locus_tag, target_symbol, M, Madj, A, pval,
# variable_in_wt, multiple_probes)
db_kemmeren_meta = read_csv("data/kemmeren/db_kemmeren_meta_20251126.csv") %>%
mutate(id = ifelse(regulator_locus_tag == 'YLR352W', 0, id)) %>%
select(id, regulator_locus_tag) %>%
distinct() %>%
mutate(id = as.integer(id)) %>%
dplyr::rename(db_id = id)
final_df_parsed_with_ids = final_parsed_df %>%
left_join(db_kemmeren_meta) %>%
replace_na(list(db_id = 0)) %>%
arrange(regulator_locus_tag) %>%
group_by(regulator_locus_tag) %>%
mutate(sample_id = cur_group_id()) %>%
relocate(sample_id, db_id,
regulator_locus_tag, regulator_symbol,
reporterId, target_locus_tag, target_symbol,
M, Madj, A, pval,
variable_in_wt, multiple_probes)
# note! verify before overwriting that the sample_id for the unique sample
# tuple is the same as it is in the current hackett_2020, or that any changes
# are intentional
# final_df_parsed_with_ids %>%
# write_parquet("~/code/hf/kemmeren_2014/kemmeren_2014.parquet",
# compression = "zstd",
# chunk_size = 6181,
# write_statistics = TRUE,
# use_dictionary = c(
# regulator_locus_tag = TRUE,
# target_locus_tag = TRUE
# )
# )
|