June 2024 classifications

DESCRIPTION

@@ -2,7 +2,6 @@ Package: pharmOncoX
 Type: Package
 Title: Molecularly targeted cancer drugs and biomarkers
 Version: 1.6.7
-Date: 2024-05-23
 Authors@R: 
     c(person(given = "Sigve",
              family = "Nakken",

NEWS.md

@@ -1,3 +1,7 @@
+# Version 1.6.8 (June 7th 2024)
+
+* NCI update (24.05d)
+
 # Version 1.6.7 (May 23rd 2024)
 
 * NCI update (24.04e)

data-raw/data-raw.R

@@ -56,7 +56,7 @@ gene_info <- dplyr::bind_rows(
     dplyr::select(gene_gencode$records$grch37, 
                   entrezgene, ensembl_gene_id),
     by = c("entrezgene"), multiple = "all")) |>
-  dplyr::filter(gene_biotype == "protein-coding") |>
+  dplyr::filter(gene_biotype == "protein_coding") |>
   dplyr::distinct() |>
   dplyr::mutate(association_sourceID = "nci_thesaurus_custom",
                 target_type = "single_protein") |>
@@ -219,7 +219,7 @@ db[['drug_map_basic']][['records']] <- drug_index_map[['id2basic']]
 db[['drug_map_alias']] <- list()
 db[['drug_map_alias']][['records']] <- drug_index_map[['id2alias']]
 
-#googledrive::drive_auth_configure(api_key = Sys.getenv("GD_KEY"))
+googledrive::drive_auth_configure(api_key = Sys.getenv("GD_KEY"))
 
 gd_records <- list()
 db_id_ref <- data.frame()

data-raw/drug_utilities.R

@@ -668,14 +668,14 @@ get_atc_drug_classification <- function(
       TRUE ~ as.character(atc_level3)
     )) |>
     dplyr::select(-atc_code_level4) |>
-    dplyr::distinct() |>
-    dplyr::mutate(atc_drug_entry = dplyr::if_else(
-      atc_code_level3 == "L01EX" |
-        atc_code_level3 == "L01FX" |
-        atc_code_level3 == "L01XX",
-      as.character(NA),
-      as.character(atc_drug_entry)
-    ))
+    dplyr::distinct() 
+    #dplyr::mutate(atc_drug_entry = dplyr::if_else(
+      #atc_code_level3 == "L01EX" |
+        #atc_code_level3 == "L01FX" |
+        #atc_code_level3 == "L01XX",
+      #as.character(NA),
+      #as.character(atc_drug_entry)
+    #))
 
   atc_custom <- as.data.frame(
     readr::read_csv(
@@ -2285,6 +2285,12 @@ assign_drug_category <- function(drug_df = NULL,
     get_atc_drug_classification(path_data_raw = path_data_raw)
 
   atc_classification_with_drugs <- atc_classification |>
+    dplyr::mutate(atc_drug_entry = dplyr::case_when(
+      !is.na(atc_drug_entry) &
+      (tolower(atc_drug_entry) == "sotorasib" |
+        tolower(atc_drug_entry) == "adagrasib") ~ as.character(NA),
+      TRUE ~ as.character(atc_drug_entry)
+    )) |>
     dplyr::filter(!is.na(atc_drug_entry))
 
   atc_classification_clean <- atc_classification |>
@@ -2404,6 +2410,8 @@ assign_drug_category <- function(drug_df = NULL,
         (!is.na(drug_name) & drug_name == "TALETRECTINIB") ~ "L01EXF",
       stringr::str_detect(
         target_symbol, "^(CHEK(1|2)\\|?){1,2}$") ~ "L01XXJ",
+      stringr::str_detect(
+        target_symbol, "^BCL2") ~ "L01XXM",
       stringr::str_detect(
         target_symbol, "^GNRH") ~ "L02AE",
       stringr::str_detect(
@@ -2514,7 +2522,7 @@ assign_drug_category <- function(drug_df = NULL,
            tolower(nci_concept_definition),
            "anthracycline|anthracenedione")) ~ "L01DB",
       (is.na(atc_code_level3) | atc_code_level3 == "NA") & 
-        stringr::str_detect(tolower(drug_entry),"hydroxyurea|eniluracil") ~ "L01BA",
+        stringr::str_detect(tolower(drug_entry),"hydroxyurea|leucovorin|eniluracil") ~ "L01BA",
       (is.na(atc_code_level3) | atc_code_level3 == "NA") & 
         stringr::str_detect(tolower(drug_entry),"arsenic trioxide") ~ "L01BA",
       (is.na(atc_code_level3) | atc_code_level3 == "NA") & 
@@ -2643,7 +2651,16 @@ assign_drug_category <- function(drug_df = NULL,
         "Other antineoplastic agents\\|Tubulin inhibitors",
         "Tubulin inhibitors"),
       as.character(atc_level3)
+    )) |>
+    dplyr::mutate(atc_level3 = dplyr::if_else(
+      !is.na(atc_level3),
+      stringr::str_replace(
+        atc_level3,
+        "Folic acid analogues|Other immunosuppressants",
+        "Folic acid analogues"),
+      as.character(atc_level3)
     ))
+
 
   classified_drugs_all_final <- classified_drugs_all |>
     dplyr::select(-atc_code_level3) |>

pkgdown/_pkgdown.yml

@@ -2,8 +2,20 @@ url: https://sigven.github.io/pharmOncoX/
 title: pharmOncoX
 toc:
   depth: 3
+
 template:
   bootstrap: 5
+  bslib:
+    info: "#BD3039"
+    dropdown-link-hover-bg: "#BD3039"
+    dropdown-link-hover-color: "white"
+    dropdown-link-active-color: "white"
+    navbar-light-color: "white"
+    navbar-light-brand-color: "white"
+    navbar-link-hover-color: "white !important"
+    nav-link-hover-color: "white !important"
+    navbar-light-brand-hover-color: "white !important"
+    navbar-link-color: "white"
   includes:
     in_header: |
        <script async src="https://www.googletagmanager.com/gtag/js?id=G-K1KDXWGEWK"></script>
@@ -13,12 +25,16 @@ template:
          gtag('js', new Date());
          gtag('config', 'G-K1KDXWGEWK');
        </script>
-  bslib:
-    primary: "#BD3039"
 authors:
   Sigve Nakken:
     href: "https://github.com/sigven"
 navbar:
+  link-color: "white"
+  light-color: "white"
+  light-brand-color: "white"
+  light-hover-color: "white !important"
+  type: light
+  bg: info
   structure:
     left:  [home, get_started, reference, news]
     right: [search, github]

pkgdown/index.md

@@ -8,14 +8,14 @@ The data is largely based on drug-target-indication associations provided by the
 
 Drug-target associations from the Open Targets Platform have furthermore been integrated and appended with drug information from [NCI Thesaurus](https://ncithesaurus.nci.nih.gov/ncitbrowser/), showing also non-targeted cancer drugs (chemotherapeutic agents etc.), and various drug regimens.
 
-_pharmOncoX_ provides anti-cancer drug classification through existing entries in the [Anatomical Therapeutic Chemical (ATC) Classification System](https://www.whocc.no/atc_ddd_index/), and these have been extended significantly with manual curation, also by establishing novel drug categories that are presently missing in the ATC classificiation tree (examples include _AURK inhibitors_, _MET inhibitors_, _BET inhibitors_, _AKT inhibitors_, _PLK inhibitors_, _IAP inhibitors_ etc.) enabling a filtering of drugs according to their main mechanisms of action.
+_pharmOncoX_ provides anti-cancer drug classification through existing entries in the [Anatomical Therapeutic Chemical (ATC) Classification System](https://www.whocc.no/atc_ddd_index/), and these have been extended significantly with manual curation, also by establishing novel drug categories that are presently missing in the ATC classificiation tree (examples include _AURK inhibitors_, _MET inhibitors_, _BET inhibitors_, _AKT inhibitors_, _PLK inhibitors_, _IAP inhibitors_, _RAS inhibitors_, _BCL2 inhibitors_ etc.) enabling a filtering of drugs according to their main mechanisms of action.
 
-Currently (as of late May 2024), `pharmOncoX` is built upon the following 
+Currently (as of early June 2024), `pharmOncoX` is built upon the following 
 releases of external databases:
 
  - Open Targets Platform (2024.03)
  - ChEMBL (v34)
- - NCI Thesaurus (24.04e)
+ - NCI Thesaurus (24.05d)
 
 ### Getting started