submitted to geo

annotated_features/batch=run_6778/part-0.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:2b1f16fae177cc6415b19eb02784d67fb84f4e221040d47a55afd4cbb584548d
+size 206481

annotated_features/batch=run_7380/part-0.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:40b614d2b44dcdad9188592ae92e9b61bae0468a724a6640e31f94ab36dec672
+size 287257

annotated_features/batch=run_7388/part-0.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:78dabc51a1f8e4d56e789843b37dfa6c35ffc6ee3d83d6466fb049632f8db096
+size 265609

annotated_features/batch=run_7390/part-0.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0bcc0b130e5cca1e98bf780eba8221e85c512f79a52f182a8411270182510396
+size 254227

annotated_features_meta.parquet

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:a2f0c27cea8819144b7ec616a6e5165dee46b94d3f6ba0de2fbe0751bf753fe7
-size 24871
+oid sha256:beb52b8eba49ee426214fd19c8b91b746085927a98a3a4152f6887773c21df8b
+size 14727

scripts/cc_sra_submission_with_addtl.R

@@ -1,15 +1,13 @@
+# All standard condition up to run_7390
+
 library(tidyverse)
 library(here)
+library(arrow)
 
-# TODO: REMOVE HYPERGEOMETRIC PVALUE FROM PROCESSED DATA
 # TODO: when making processing scripts github, add the background file
 # and make sure the repo gets registered to zenodo. Put that link to the
 # background files in the SRA submission
 
-# for "data_usable" in sra submission, change to "perturbation_validated".
-# factor levels should be "true", "false", "unreviewed" (DTO only)
-# num_insertions for number of insertions
-#
 # cells grown on solid media at room temperature
 # put the definition of the "Description" values in the
 
@@ -35,9 +33,12 @@ analysis_set_meta = read_csv("~/htcf_ref/data/yeast_database_modelling/pull_data
 composite_binding = read_csv("~/htcf_ref/data/yeast_database_modelling/pull_data_20250805/data/bindingconcat_meta_20250805.csv") %>%
     filter(source_name == "brent_nf_cc")
 
-barcode_details_list = list.files("~/htcf_local/cc/yeast/data", "*_barcode_details.json",
+barcode_details_root = "~/htcf_lts/sequence_data/yeast_cc/sequence"
+barcode_details_list = list.files(barcode_details_root, "*_barcode_details.json",
                                   recursive=TRUE)
 
+passing_bam_paths = read_csv("~/htcf_local/cc/yeast/passing_bams_lookup.txt", col_names = 'bampath')
+
 passing_fastq_from_bam_paths = list.files("~/htcf_local/cc/yeast/passing_fastq_from_bam")
 
 fastq_df = tibble(filename = passing_fastq_from_bam_paths) %>%
@@ -58,7 +59,7 @@ fastq_df = tibble(filename = passing_fastq_from_bam_paths) %>%
 
 barcode_details_df = map(barcode_details_list, ~{
     message(sprintf("working on %s", basename(.x)))
-    x = jsonlite::read_json(file.path("~/htcf_local/cc/yeast/data", .))
+    x = jsonlite::read_json(file.path(barcode_details_root, .))
     tibble(
         seq = names(x$components$tf$map),
         regulator_symbol = unlist(x$components$tf$map)) %>%
@@ -80,6 +81,16 @@ binding_django = read_csv(here("data/binding_from_django_db_20260128.csv"))
 
 barcode_details_df_with_id = barcode_details_df %>%
     mutate(replicate = str_remove(str_extract(regulator_symbol, "x\\d"), "x")) %>%
+    mutate(condition = case_when(
+        batch == "run_7380" & replicate == 2 ~ 'del_MET28',
+        regulator_symbol == "CBF1KOmet28" ~ 'del_MET28',
+        batch == "run_7380" & replicate == 2 ~ 'glu_1_gal_2',
+        batch == "run_7388" & replicate == 2 ~ 'glu_1_gal_2',
+        batch == "run_7390" & replicate == 2 ~ 'glu_1_gal_2',
+        batch == "run_7392" & replicate == 2 ~ 'glu_1_gal_2',
+        .default = 'standard')) %>%
+    mutate(replicate = ifelse(condition != "standard", 1, replicate)) %>%
+    mutate(regulator_symbol = ifelse(regulator_symbol == 'CBF1KOmet28', "CBF1", regulator_symbol)) %>%
     mutate(regulator_symbol = str_remove(regulator_symbol, "x\\d")) %>%
     replace_na(list(replicate = '1')) %>%
     mutate(replicate = as.integer(replicate)) %>%
@@ -99,8 +110,10 @@ setdiff(basename(c(brentlab_dirs, mitra_dirs)), unique(binding_django$batch))
 
 gm_db = arrow::open_dataset("~/code/hf/callingcards/genome_map")
 
-genome_map_meta = arrow::read_parquet("~/code/hf/callingcards/genome_map_meta.parquet") %>%
-    # filter(condition == "standard") %>%
+genome_map_meta_raw = arrow::read_parquet("~/code/hf/callingcards/genome_map_meta.parquet")
+
+genome_map_meta = genome_map_meta_raw %>%
+    filter(condition == "standard") %>%
     filter(!batch %in% c('dsir4'))
 
 fastq_df_with_id = fastq_df %>%
@@ -108,15 +121,46 @@ fastq_df_with_id = fastq_df %>%
                   mutate(regulator_symbol = ifelse(str_detect(regulator_symbol, "unknown"),
                                                    regulator_locus_tag,
                                                    regulator_symbol))) %>%
-    filter(condition == 'standard')
-
-fastq_df_with_id %>%
-    filter(binding_id == "NA") %>%
-    filter(condition == "standard") %>%
-    filter(regulator_symbol != "OTU1") %>%
-    mutate(qbed_path = file.path(sprintf("/home/chase/htcf_local/cc/yeast/results/%s/hops/%s_%s.qbed", batch, batch, regulator_symbol_replicate))) %>%
-    select(qbed_path) %>%
-    write_tsv("~/tmp/unprocessed_in_db_qbeds_lookup.txt")
+    filter(condition == 'standard') %>%
+    filter(batch != "run_7392")
+
+fastq_df_lookup = fastq_df_with_id %>%
+    mutate(filename = file.path("passing_fastq_from_bam", filename),
+           newname =  paste0(regulator_locus_tag, "_", regulator_symbol, "_", id)) %>%
+    select(filename, newname)
+
+bam_lookup = passing_bam_paths %>%
+    mutate(base = str_remove(basename(bampath), ".bam")) %>%
+    # this is empty, also excluded from the fastqs
+    filter(base != "run_6739_MOT3_passing_tagged") %>%
+    left_join(fastq_df_lookup %>%
+                  mutate(base = str_remove(basename(filename), ".fastq.gz"))) %>%
+    filter(str_detect(bampath, "undetermined", negate=TRUE)) %>%
+    select(-filename) %>%
+    # this removes the non standard conditions
+    filter(complete.cases(.))
+
+setdiff(bam_lookup$newname, fastq_df_lookup$newname)
+setdiff(fastq_df_lookup$newname, bam_lookup$newname)
+
+# bam_lookup %>%
+#     select(bampath, newname) %>%
+#     mutate(newname = paste0(newname, ".bam")) %>%
+#     write_tsv("~/htcf_local/cc/yeast/passing_bam_rename_lookup.txt",
+#               col_names = FALSE)
+
+# fastq_df_lookup %>%
+#     write_tsv("~/htcf_local/cc/yeast/passing_bam_fastq_rename_lookup.txt",
+#               col_names = FALSE)
+
+
+# fastq_df_with_id %>%
+#     filter(binding_id == "NA") %>%
+#     filter(condition == "standard") %>%
+#     filter(regulator_symbol != "OTU1") %>%
+#     mutate(qbed_path = file.path(sprintf("/home/chase/htcf_local/cc/yeast/results/%s/hops/%s_%s.qbed", batch, batch, regulator_symbol_replicate))) %>%
+#     select(qbed_path) %>%
+#     write_tsv("~/tmp/unprocessed_in_db_qbeds_lookup.txt")
 
 
 # ACE2, ARG80, ARG81, LYS14, STB5, SWI5, SWI6 pass in at least one (didn't check which mcisaac cond pass, but all pass in kemmeren pass)
@@ -151,7 +195,7 @@ af_django_meta = arrow::read_parquet("~/code/hf/callingcards/annotated_features_
                   distinct() %>%
                   mutate(single_binding = as.character(single_binding)) %>%
                   dplyr::rename(binding_id = single_binding)) %>%
-    left_join(select(barcode_details_df_with_id, regulator_symbol, batch, binding_id, r1_index, r2_index)) %>%
+    left_join(select(barcode_details_df_with_id, condition, regulator_symbol, batch, binding_id, r1_index, r2_index)) %>%
     dplyr::select(id, genome_map_id, batch,
                   r1_index, r2_index,
                   regulator_locus_tag, regulator_symbol,
@@ -174,10 +218,6 @@ setdiff(unique(genome_map_meta$batch),basename(c(brentlab_dirs, mitra_dirs)))
 #     filter(id == 1) %>%
 #     collect()
 
-library(arrow)
-library(dplyr)
-library(readr)
-
 # Specify output directory
 # output_dir <- here("~/htcf_local/cc/yeast/callingcards_geo_submission/processed")
 # dir.create(output_dir, showWarnings = FALSE, recursive = TRUE)
@@ -215,33 +255,175 @@ id_batch_combos <- af_django_meta %>%
 #
 # cat("Done! Wrote", nrow(id_batch_combos), "CSV files to", output_dir, "\n")
 
+af_data = arrow::open_dataset("~/code/hf/callingcards/annotated_features") %>%
+    filter(id %in% af_django_meta$id) %>%
+    collect() %>%
+    left_join(
+        af_django_meta %>%
+            mutate(regulator_locus_tag = as.character(regulator_locus_tag),
+                   regulator_symbol = as.character(regulator_symbol)) %>%
+            mutate(regulator_symbol = ifelse(str_detect(regulator_symbol, "unknown"), regulator_locus_tag, regulator_symbol)) %>%
+            mutate(filename = paste0(regulator_locus_tag, "_", regulator_symbol, "_", genome_map_id)) %>%
+            select(id, genome_map_id, filename))
+
+promoters = read_tsv("~/code/hf/yeast_genome_resources/yiming_promoters.bed",
+                     col_names = c("chr", "start", "end", "target_locus_tag", "score", "strand")) %>%
+    dplyr::select(target_locus_tag, chr, start, end, strand)
+
+# af_data %>%
+#     group_by(filename) %>%
+#     group_walk(~ {
+#         dir.create(here("results/processed"), showWarnings = FALSE)
+#         output_name = paste0(.y$filename, ".csv.gz")
+#         .x %>%
+#             mutate(target_symbol = ifelse(str_detect(target_symbol, "unknown"), target_locus_tag, target_symbol)) %>%
+#             dplyr::select(-c(id, hypergeometric_pval, batch)) %>%
+#             dplyr::rename(enrichment = callingcards_enrichment) %>%
+#             left_join(promoters) %>%
+#             dplyr::relocate(genome_map_id, target_locus_tag, target_symbol, chr, start, end, strand) %>%
+#         write_csv(file.path(here("results/processed"), output_name))
+#     })
+
+
 submission_df = af_django_meta %>%
     select(-id) %>%
     arrange(regulator_locus_tag) %>%
+    mutate(regulator_locus_tag = as.character(regulator_locus_tag),
+           regulator_symbol = as.character(regulator_symbol)) %>%
     mutate(regulator_symbol = ifelse(
         str_detect(regulator_symbol, "unknown"),
         regulator_locus_tag,
         regulator_symbol)) %>%
     mutate(`library name` = paste0(regulator_locus_tag, "_", regulator_symbol, "_", genome_map_id)) %>%
-    mutate(title = paste0(regulator_locus_tag, " (", regulator_symbol, ") calling cards"),
-           `library strategy` = "CallingCards",
+    mutate(title = paste0(regulator_locus_tag, " (", regulator_symbol, ") calling cards; gmid ", genome_map_id),
+           `library strategy` = "OTHER",
            organism = 'Saccharomyces cerevisiae',
-           strain = '',
+           `cell line` = "Saccharomyces cerevisiae S288C",
            molecule = 'genomic DNA',
-           `single or paired-end` = 'single-end',
-           `instrument model` = 'illumina MiSeq i100',
+           `single or paired-end` = 'single',
+           `instrument model` = 'Illumina MiSeq',
            description = paste0(regulator_locus_tag, " tagged callingcards experiment. ",
                                 "kemmeren_dto: ", kemmeren_dto, "; mcisaac_dto: ", mcisaac_dto,
-                                "; genomic_inserts: ", genomic_inserts,
                                 "; in_modeling_analysis: ", in_modeling_analysis,
                                 "; notes: ", notes),
            `processed data file` =  paste0(`library name`, ".csv.gz"),
-           `raw file` = paste0(`library name`, ".fastq.gz")) %>%
+           `raw file` = paste0(`library name`, ".bam")) %>%
+    dplyr::rename(perturbation_validated = data_usable) %>%
     dplyr::select(
-        `library name`, title, `library strategy`, organism,
-        strain, molecule, `single or paired-end`, `instrument model`,
-        description,
+        `library name`, title, `library strategy`, organism, `cell line`,
+        molecule, `single or paired-end`, `instrument model`,
+        description, perturbation_validated,
         `processed data file`, `raw file`
     )
 
-# write_csv(submission_df, here("data/cc_submission_df.csv"))
+setdiff(paste0(bam_lookup$newname,".bam"), submission_df$`raw file`)
+setdiff(submission_df$`raw file`, paste0(bam_lookup$newname,".bam"))
+
+write_csv(submission_df, here("data/cc_submission_df.csv"))
+
+################################################################################
+################################################################################
+################################################################################
+# library(tidyverse)
+# library(arrow)
+# library(here)
+#
+# genome_map_meta = arrow::read_parquet("~/code/hf/callingcards/genome_map_meta.parquet")
+#
+# genome_map_meta_af = genome_map_meta %>% filter(batch %in% c("run_6778", "run_7380", "run_7388", "run_7390"))
+#
+# af = list.files("~/tmp/callingcards_output", full.names = TRUE)
+#
+# af_gmid_map = tibble(
+#     af = str_remove(basename(af), "_af.csv"),
+#     batch = str_extract(af, "run_\\d+"),
+#     regulator_orig = str_remove(af, paste0(batch, "_")),
+#     regulator_symbol = str_remove(regulator_orig, "x\\d")) %>%
+#     mutate(regulator_symbol = ifelse(regulator_symbol == 'CBF1KOmet28', "CBF1", regulator_symbol)) %>%
+#     mutate(condition = case_when(
+#         str_detect(regulator_orig, "x\\d$", negate=TRUE) | str_detect(regulator_orig, "x1$") ~ 'standard',
+#         regulator_orig == 'CBF1x2' ~ 'del_MET28',
+#         regulator_orig == 'CBF1KOmet28' ~ 'del_MET28',
+#         regulator_orig == 'GCR1x2' ~ 'glu_1_gal_2',
+#         regulator_orig == 'GCR2x2' ~ 'glu_1_gal_2',
+#         regulator_orig == 'TYE7x2' ~ 'glu_1_gal_2',
+#         regulator_orig == "MIG1x2" ~ 'glu_1_gal_2')) %>%
+#     left_join(dplyr::select(genome_map_meta_af, batch, regulator_symbol, condition, id)) %>%
+#     mutate(id = ifelse(regulator_orig == 'CBF1KOmet28', 746, id))
+#
+#
+# af_df = map(af, read_csv)
+# names(af_df) = af_gmid_map$id
+#
+# genomicfeatures = arrow::read_parquet("~/code/hf/yeast_genome_resources/brentlab_features.parquet")
+#
+# promoters = read_tsv("~/code/hf/yeast_genome_resources/yiming_promoters.bed",
+#                      col_names = c("chr", "start", "end", "name", "score", "strand")) %>%
+#     dplyr::select("chr", "name", "start", "end", "strand") %>%
+#     left_join(dplyr::select(genomicfeatures, name = locus_tag, symbol))
+#
+# af_df_all = bind_rows(af_df, .id = "genome_map_id") %>%
+#     mutate(genome_map_id = as.integer(genome_map_id)) %>%
+#     dplyr::select(c(
+#         'genome_map_id','name','experiment_hops',
+#         'background_hops','background_total_hops','experiment_total_hops',
+#         'callingcards_enrichment','poisson_pval','hypergeometric_pval')) %>%
+#     left_join(promoters) %>%
+#     dplyr::rename(target_locus_tag = name, target_symbol = symbol) %>%
+#     dplyr::select(
+#         c('genome_map_id','target_locus_tag','target_symbol','experiment_hops',
+#         'background_hops','background_total_hops','experiment_total_hops',
+#         'callingcards_enrichment','poisson_pval','hypergeometric_pval')) %>%
+#     left_join(dplyr::select(af_gmid_map, id, batch), by = c("genome_map_id" = "id")) %>%
+#     mutate(genome_map_id = as.integer(genome_map_id))
+#
+# af_meta = arrow::read_parquet('~/code/hf/callingcards/annotated_features_meta.parquet')
+#
+# af_meta_new = af_gmid_map %>%
+#     dplyr::select(id, batch, regulator_symbol, condition) %>%
+#     dplyr::rename(genome_map_id = id) %>%
+#     left_join(dplyr::select(genomicfeatures,
+#                             regulator_locus_tag = locus_tag,
+#                             regulator_symbol = symbol)) %>%
+#     mutate(data_usable = 'unreviewed', analysis_set = FALSE) %>%
+#     # note that this is 810 before adding these records
+#     mutate(id = max(af_meta$id)+row_number(),
+#            pss_id = "NA",
+#            binding_id = "NA") %>%
+#     dplyr::relocate(id)
+#
+# af_meta_augment = af_meta %>%
+#     dplyr::select(-preferred_replicate) %>%
+#     bind_rows(af_meta_new) %>%
+#     replace_na(list(binding_id = "NA"))
+#
+# # af_meta_augment |>
+# #     arrow::as_arrow_table() |>
+# #     (\(tbl) {
+# #         dict_cols <- c("data_usable", "batch", "condition", "regulator_locus_tag", "regulator_symbol")
+# #         for (col in dict_cols) {
+# #             tbl[[col]] <- tbl[[col]]$cast(arrow::dictionary())
+# #         }
+# #         tbl
+# #     })() |>
+# #     arrow::as_arrow_table() |>
+# #     arrow::write_parquet(
+# #         "/home/chase/code/hf/callingcards/annotated_features_meta.parquet",
+# #         compression = "zstd",
+# #         compression_level = 9,
+# #         write_statistics = TRUE
+# #     )
+# #
+# # af_df_all %>%
+# #     left_join(dplyr::select(af_meta_new, id, genome_map_id)) %>%
+# #     dplyr::relocate(id) %>%
+# #     select(-genome_map_id) %>%
+# #     arrow::write_dataset(
+# #         path = "/home/chase/code/hf/callingcards/annotated_features_tmp",
+# #         format = "parquet",
+# #         partitioning = c("batch"),
+# #         existing_data_behavior = "error",
+# #         compression = "zstd",
+# #         compression_level = 9,
+# #         write_statistics = TRUE,
+# #         use_dictionary = TRUE)