callingcards / scripts /separate_composite.R
cmatkhan's picture
separating the combined data to ites own dataset
61f35aa
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)