src/01_get_condig_gene.py: fix the gtf used

src/01_get_condig_gene.py

@@ -15,7 +15,7 @@ import pandas as pd
 ##################
 
 GTF = Path(__file__).parents[1] / "data" / \
-    "GCF_000001405.40_GRCh38.p14_genomic.gtf"
+    "GCF_000001405.39_GRCh38.p13_genomic.gtf_coding_annotation.gtf"
 OUTPUT = Path(__file__).parents[1] / "results" / "coding_genes"
 
 

src/06_compute_tdd_index.R

@@ -36,19 +36,19 @@ compute_tdd <- function(treatment = "BRAF", mean_gene_count = 10, ercc = F) {
     )
     if (mean_gene_count > 0) {
         norm_df$rmean <- norm_df %>%
-            select(-gene) %>%
+            dplyr::select(-gene) %>%
             rowMeans()
         norm_df <- norm_df %>% filter(rmean >= mean_gene_count) # nolint
-        norm_df <- norm_df %>% select(-rmean) # nolint
+        norm_df <- norm_df %>% dplyr::select(-rmean) # nolint
     }
     norm_df$rmin <- norm_df %>%
-        select(-gene) %>%
+        dplyr::select(-gene) %>%
         apply(1, min)
     norm_df <- norm_df %>% filter(rmin > 0) # nolint
-    norm_df <- norm_df %>% select(-rmin) # nolint
+    norm_df <- norm_df %>% dplyr::select(-rmin) # nolint
 
     rep <- norm_df %>%
-        select(-gene) %>%
+        dplyr::select(-gene) %>%
         colnames() %>%
         str_extract("X...") %>%
         unique()
@@ -111,7 +111,7 @@ create_density_figs <- function(tdd_tibble, treatment = "BRAF",
                                 ercc = F) {
     dir.create(output_folder, showWarnings = F)
     rep <- tdd_tibble %>%
-        select(-gene) %>%
+        dplyr::select(-gene) %>%
         colnames() %>%
         str_extract("X...") %>%
         unique()
@@ -387,10 +387,10 @@ get_cor_value <- function(tdd_full, my_group = "BRAF_DOWN") {
     tdd <- tdd_full %>% filter(group == my_group) ## nolint
     c <- cor(
         tdd %>% filter(group == my_group) %>% # nolint
-            select(mean_DMSO_TDD) %>% unlist(), # nolint
+            dplyr::select(mean_DMSO_TDD) %>% unlist(), # nolint
         tdd %>%
             filter(group == my_group) %>% # nolint
-            select(mean_BRAF_TDD) %>%
+            dplyr::select(mean_BRAF_TDD) %>%
             unlist() # nolint
     )
     res <- coef(lm(mean_BRAF_TDD ~ mean_DMSO_TDD, tdd %>%
@@ -415,12 +415,13 @@ prepare_df_for_cor <- function(mean_gene_count = 10, ercc = F,
     ]
     tdd_full <- tdd_full %>%
         mutate(p_value = apply(
-            tdd_full %>% select(starts_with("X")), 1,
+            tdd_full %>% dplyr::select(starts_with("X")), 1,
             function(x) {
                 t_test_func(x)
             }
         )) # nolint
     tdd_full <- tdd_full %>% arrange(-p_value) # nolint
+    write_tsv(tdd_full, paste0(output_folder, "/full_TDD_correlation_table.txt"))
     dir <- "./data/gene_lists/"
     down_braf <- read.table(paste0(dir, "BRAF_DOWN_1.5_name.txt"))$V1
     up_braf <- read.table(paste0(dir, "BRAF_UP_1.5_name.txt"))$V1
@@ -436,11 +437,11 @@ prepare_df_for_cor <- function(mean_gene_count = 10, ercc = F,
     write_tsv(tdd_full, paste0(output_folder, "/TDD_correlation_table.txt")) # nolint
     tdd_full %>%
         filter(kind == "BRAF_DOWN_sig", mean_BRAF_TDD > mean_DMSO_TDD) %>%
-        select(gene) %>%
+        dplyr::select(gene) %>%
         write_tsv(paste0(output_folder, "/TDD_BRAF_BRAF_DOWN.txt"))
     tdd_full %>%
         filter(kind == "BRAF_UP_sig", mean_DMSO_TDD > mean_BRAF_TDD) %>%
-        select(gene) %>%
+        dplyr::select(gene) %>%
         write_tsv(paste0(output_folder, "/TDD_DMSO_BRAF_UP.txt"))
     return(tdd_full)
 }
@@ -609,7 +610,7 @@ create_peaks_barplots <- function(tdd_filt, pval_glm_nb, output_fig,
             ifelse(!!as.symbol(data_col) > 0, 1, 0)
     )
     tdd_fig <- tdd_filt %>%
-        select(!!as.symbol(data_col), !!as.symbol(has_col), group) %>%
+        dplyr::select(!!as.symbol(data_col), !!as.symbol(has_col), group) %>%
         group_by(group) %>%
         summarise(
             !!as.symbol(res_col) := mean(!!as.symbol(data_col)),
@@ -772,7 +773,7 @@ get_peak_df <- function(peak_file, kind = "peak") {
         )
         peak_table <- peak_table %>%
             mutate(size = stop - start) %>%
-            select(c(gene, size)) %>%
+            dplyr::select(c(gene, size)) %>%
             group_by(gene) %>%
             summarise(peak_surface = sum(size))
     }
@@ -808,7 +809,7 @@ get_tdd_pic_table <- function(peak_file, mean_gene_count = 10, ercc = F,
             TDD_BRAF = gene %in% tdd_braf_braf_down$gene,
             TDD_DMSO = gene %in% tdd_dmso_braf_up$gene
         ) %>%
-        select(gene, TDD_BRAF, TDD_DMSO) # nolint
+        dplyr::select(gene, TDD_BRAF, TDD_DMSO) # nolint
     tdd_full <- tdd_full %>% left_join(peak_table) # nolint
     tdd_full <- tdd_full %>% replace_na(list(peak = 0, peak_surface = 0)) # nolint
     return(tdd_full)