Datasets:

BrentLab
/

callingcards

library(tidyverse)
library(arrow)

meta = arrow::read_parquet("~/code/hf/callingcards/annotated_features_meta.parquet")

composite_meta = meta %>%
    filter(batch == "composite")

binding_id_to_genome_map_id = meta %>%
    select(genome_map_id, binding_id) %>%
    filter(complete.cases(.)) %>%
    distinct()

composite_binding_id_to_composite_genome_map_id = composite_meta %>%
    select(binding_id) %>%
    mutate(genome_map_id_set = map(binding_id, function(bid_str) {
        # Parse the JSON-like string to extract individual binding_ids
        bid_vec = str_extract_all(bid_str, "\\d+")[[1]]
        # Look up corresponding genome_map_ids
        binding_id_to_genome_map_id %>%
            filter(binding_id %in% bid_vec) %>%
            pull(genome_map_id)})) %>%
    mutate(genome_map_id_set = map_chr(genome_map_id_set, ~paste(.x, collapse = "-")))

composite_meta_revise = composite_meta %>%
    select(-genome_map_id) %>%
    left_join(composite_binding_id_to_composite_genome_map_id) %>%
    dplyr::relocate(genome_map_id_set)

af_data = arrow::open_dataset("~/code/hf/callingcards/annotated_features") %>%
    filter(id %in% composite_meta_revise$id) %>%
    collect() %>%
    select(-batch) %>%
    left_join(composite_meta_revise %>%
                  select(id, genome_map_id_set)) %>%
    select(-id) %>%
    dplyr::relocate(genome_map_id_set)

# composite_meta_revise %>%
#     select(-id) %>%
#     dplyr::relocate(genome_map_id_set) %>%
#     arrow::write_parquet(
#         "~/code/hf/callingcards/annotated_features_combined_meta.parquet",
#         compression = "zstd",
#         write_statistics = TRUE,
#         use_dictionary = c(
#             regulator_locus_tag = TRUE,
#             regulator_symbol = TRUE,
#             condition = TRUE))
#
# arrow::write_dataset(
#     af_data,
#     path = "/home/chase/code/hf/callingcards/annotated_features_combined",
#     format = "parquet",
#     partitioning = c("genome_map_id_set"),
#     existing_data_behavior = "overwrite",
#     compression = "zstd",
#     write_statistics = TRUE)

	library(tidyverse)
	library(arrow)

	meta = arrow::read_parquet("~/code/hf/callingcards/annotated_features_meta.parquet")

	composite_meta = meta %>%
	filter(batch == "composite")

	binding_id_to_genome_map_id = meta %>%
	select(genome_map_id, binding_id) %>%
	filter(complete.cases(.)) %>%
	distinct()

	composite_binding_id_to_composite_genome_map_id = composite_meta %>%
	select(binding_id) %>%
	mutate(genome_map_id_set = map(binding_id, function(bid_str) {
	# Parse the JSON-like string to extract individual binding_ids
	bid_vec = str_extract_all(bid_str, "\\d+")[[1]]
	# Look up corresponding genome_map_ids
	binding_id_to_genome_map_id %>%
	filter(binding_id %in% bid_vec) %>%
	pull(genome_map_id)})) %>%
	mutate(genome_map_id_set = map_chr(genome_map_id_set, ~paste(.x, collapse = "-")))

	composite_meta_revise = composite_meta %>%
	select(-genome_map_id) %>%
	left_join(composite_binding_id_to_composite_genome_map_id) %>%
	dplyr::relocate(genome_map_id_set)

	af_data = arrow::open_dataset("~/code/hf/callingcards/annotated_features") %>%
	filter(id %in% composite_meta_revise$id) %>%
	collect() %>%
	select(-batch) %>%
	left_join(composite_meta_revise %>%
	select(id, genome_map_id_set)) %>%
	select(-id) %>%
	dplyr::relocate(genome_map_id_set)

	# composite_meta_revise %>%
	# select(-id) %>%
	# dplyr::relocate(genome_map_id_set) %>%
	# arrow::write_parquet(
	# "~/code/hf/callingcards/annotated_features_combined_meta.parquet",
	# compression = "zstd",
	# write_statistics = TRUE,
	# use_dictionary = c(
	# regulator_locus_tag = TRUE,
	# regulator_symbol = TRUE,
	# condition = TRUE))
	#
	# arrow::write_dataset(
	# af_data,
	# path = "/home/chase/code/hf/callingcards/annotated_features_combined",
	# format = "parquet",
	# partitioning = c("genome_map_id_set"),
	# existing_data_behavior = "overwrite",
	# compression = "zstd",
	# write_statistics = TRUE)