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library(furrr)
library(here)
dto_results_lookup = expand_grid(
pr_source = c("hackett", "hughes_oe", "hughes_ko", "hu_reimand", "kemmeren", "mahendrawada_rnaseq"),
# binding_source = c("cc", "chipexo", "harbison", "mahendrawada_chec"),
binding_source = c("cc", "chipexo", "mahendrawada_chec"),
pr_ranking_column = c("effect", "pvalue")) %>%
mutate(
result_file = map(file.path(here("results/processed"),
pr_source,
binding_source, "results",
pr_ranking_column),
~list.files(.x, full.names = TRUE))) %>%
unnest(result_file) %>%
mutate(tmp = str_remove(basename(result_file), "_results.json")) %>%
separate_wider_delim(tmp,
names = c('binding_id', 'perturbation_id'),
delim = "-_-")
plan(multisession, workers = 20)
# Function with retry logic
read_json_with_retry = function(filepath, max_retries = 1) {
for (attempt in 1:max_retries) {
result = tryCatch({
pivot_wider(enframe(as_vector(jsonlite::read_json(filepath))))
}, error = function(e) {
if (attempt < max_retries) {
message(sprintf("Attempt %d/%d failed for %s: %s. Retrying...",
attempt, max_retries, filepath, e$message))
Sys.sleep(2^(attempt - 1)) # Exponential backoff: 1s, 2s, 4s, 8s, 16s
NULL
} else {
stop(sprintf("Failed after %d attempts for file: %s\nError: %s",
max_retries, filepath, e$message))
}
})
if (!is.null(result)) {
return(result)
}
}
}
dto_results_list = future_imap(dto_results_lookup$result_file, ~{
tryCatch({
# Check if file is empty
if (file.size(.x) == 0) {
return(tibble(
empirical_pvalue = NA_real_,
fdr = NA_real_,
population_size = NA_real_,
rank1 = NA_real_,
rank2 = NA_real_,
set1_len = NA_real_,
set2_len = NA_real_,
unpermuted_intersection_size = NA_real_,
unpermuted_pvalue = NA_real_
))
}
read_json_with_retry(.x)
}, error = function(e) {
stop(sprintf("Index %d failed:\nFile: %s\nError: %s",
.y, .x, e$message))
})
}, .progress = TRUE, .options = furrr_options(seed = TRUE))
dto_results_df = bind_cols(dto_results_lookup, bind_rows(dto_results_list))
hf_results_df = dto_results_df %>%
mutate(
binding_id = case_when(
binding_source == "cc"
~ paste0("BrentLab/callingcards;annotated_feature_reprocess_mindel;",
binding_id),
binding_source == "chipexo"
~ paste0("BrentLab/rossi_2021;rossi_2021_af_combined_mindel;",
binding_id),
binding_source == "mahendrawada_chec"
~ paste0("BrentLab/mahendrawada_2025;chec_mahendrawada_m2025_af_combined_mindel;",
binding_id)),
perturbation_id = case_when(
pr_source == "hackett" ~ paste0("BrentLab/hackett_2020;hackett_2020;", perturbation_id),
pr_source == "hughes_oe" ~ paste0("BrentLab/hughes_2006;overexpression;", perturbation_id),
pr_source == "hughes_ko" ~ paste0("BrentLab/hughes_2006;knockout;", perturbation_id),
pr_source == "hu_reimand" ~ paste0("BrentLab/hu_2007_reimand_2010;hu_2007_reimand_2010;", perturbation_id),
pr_source == "kemmeren" ~ paste0("BrentLab/kemmeren_2014;kemmeren_2014;", perturbation_id),
pr_source == "mahendrawada_rnaseq" ~ paste0("BrentLab/mahendrawada_2025;rnaseq_reprocessed;", perturbation_id),
.default = "ERROR"),
binding_repo_dataset = case_when(
binding_source == "cc"
~ "callingcards-annotated_feature_reprocess_mindel",
binding_source == "chipexo"
~ "rossi_2021-rossi_2021_af_combined_mindel",
binding_source == "harbison"
~ paste0("harbison_2004-harbison_2004"),
binding_source == "mahendrawada_chec"
~ "mahendrawada_2025-chec_mahendrawada_m2025_af_combined_mindel"),
perturbation_repo_dataset = case_when(
pr_source == "hackett" ~ paste0("hackett_2020-hackett_2020"),
pr_source == "hughes_oe" ~ paste0("hughes_2006-overexpression"),
pr_source == "hughes_ko" ~ paste0("hughes_2006-knockout"),
pr_source == "hu_reimand" ~ paste0("hu_2007_reimand_2010-hu_2007_reimand_2010"),
pr_source == "kemmeren" ~ paste0("kemmeren_2014-kemmeren_2014"),
pr_source == "mahendrawada_rnaseq" ~ paste0("mahendrawada_2025-rnaseq_reprocessed"),
.default = "ERROR")) %>%
dplyr::rename(binding_rank_threshold = rank1,
perturbation_rank_threshold = rank2,
binding_set_size = set1_len,
perturbation_set_size = set2_len,
dto_fdr = fdr,
dto_empirical_pvalue = empirical_pvalue) %>%
select(binding_id, perturbation_id,
binding_rank_threshold, perturbation_rank_threshold,
binding_set_size, perturbation_set_size,
dto_fdr, dto_empirical_pvalue,
pr_ranking_column,
binding_repo_dataset, perturbation_repo_dataset)
# arrow::write_dataset(
# hf_results_df,
# path = "/home/chase/code/hf/yeast_comparative_analysis/dto_rossi_cc_mahendrawada_mindel",
# format = "parquet",
# partitioning = c("binding_repo_dataset", "perturbation_repo_dataset"),
# existing_data_behavior = "overwrite",
# compression = "zstd",
# write_statistics = TRUE,
# use_dictionary = c(
# binding_id = TRUE,
# perturbation_id = TRUE
# )
# )
# hf_results_df = dto_results_df %>%
# mutate(
# binding_id = case_when(
# binding_source == "cc" & str_detect(binding_id, "-")
# ~ paste0("BrentLab/callingcards;annotated_features_combined;",
# binding_id),
# binding_source == "cc" & str_detect(binding_id, "-", negate=TRUE)
# ~ paste0("BrentLab/callingcards;annotated_features;",
# binding_id),
# binding_source == "chipexo"
# ~ paste0("BrentLab/rossi_2021;rossi_2021_af_combined;",
# binding_id),
# binding_source == "harbison"
# ~ paste0("BrentLab/harbison_2004;harbison_2004;",
# binding_id),
# binding_source == "mahendrawada_chec"
# ~ paste0("BrentLab/mahendrawada_2025;chec_mahendrawada_m2025_af_combined;",
# binding_id)),
# perturbation_id = case_when(
# pr_source == "hackett" ~ paste0("BrentLab/hackett_2020;hackett_2020;", perturbation_id),
# pr_source == "hughes_oe" ~ paste0("BrentLab/hughes_2006;overexpression;", perturbation_id),
# pr_source == "hughes_ko" ~ paste0("BrentLab/hughes_2006;knockout;", perturbation_id),
# pr_source == "hu_reimand" ~ paste0("BrentLab/hu_2007_reimand_2010;hu_2007_reimand_2010;", perturbation_id),
# pr_source == "kemmeren" ~ paste0("BrentLab/kemmeren_2014;kemmeren_2014;", perturbation_id),
# pr_source == "mahendrawada_rnaseq" ~ paste0("BrentLab/mahendrawada_2025;rnaseq_reprocessed;", perturbation_id),
# .default = "ERROR"),
# binding_repo_dataset = case_when(
# binding_source == "cc" & str_detect(binding_id, "-")
# ~ "callingcards-annotated_features_combined",
# binding_source == "cc" & str_detect(binding_id, "-", negate=TRUE)
# ~ "callingcards-annotated_features",
# binding_source == "chipexo"
# ~ "rossi_2021-rossi_2021_af_combined",
# binding_source == "harbison"
# ~ paste0("harbison_2004-harbison_2004"),
# binding_source == "mahendrawada_chec"
# ~ "mahendrawada_2025-chec_mahendrawada_m2025_af_combined"),
# perturbation_repo_dataset = case_when(
# pr_source == "hackett" ~ paste0("hackett_2020-hackett_2020"),
# pr_source == "hughes_oe" ~ paste0("hughes_2006-overexpression"),
# pr_source == "hughes_ko" ~ paste0("hughes_2006-knockout"),
# pr_source == "hu_reimand" ~ paste0("hu_2007_reimand_2010-hu_2007_reimand_2010"),
# pr_source == "kemmeren" ~ paste0("kemmeren_2014-kemmeren_2014"),
# pr_source == "mahendrawada_rnaseq" ~ paste0("mahendrawada_2025-rnaseq_reprocessed"),
# .default = "ERROR")) %>%
# dplyr::rename(binding_rank_threshold = rank1,
# perturbation_rank_threshold = rank2,
# binding_set_size = set1_len,
# perturbation_set_size = set2_len,
# dto_fdr = fdr,
# dto_empirical_pvalue = empirical_pvalue) %>%
# select(binding_id, perturbation_id,
# binding_rank_threshold, perturbation_rank_threshold,
# binding_set_size, perturbation_set_size,
# dto_fdr, dto_empirical_pvalue,
# pr_ranking_column,
# binding_repo_dataset, perturbation_repo_dataset)
# note that the deprecated directory is ignored in yeast_comparative_analysis.
# this exists on my computer and could exist on yours, too, if you wanted to
# put old results in a subdir called deprecated that would be ignored by huggingface/git
# old_db_dto_res = arrow::open_dataset("~/code/hf/yeast_comparative_analysis/deprecated/dto") %>%
# collect()
# arrow::write_dataset(
# hf_results_df,
# path = "/home/chase/code/hf/yeast_comparative_analysis/dto",
# format = "parquet",
# partitioning = c("binding_repo_dataset", "perturbation_repo_dataset"),
# existing_data_behavior = "overwrite",
# compression = "zstd",
# write_statistics = TRUE,
# use_dictionary = c(
# binding_id = TRUE,
# perturbation_id = TRUE
# )
# )
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