diff --git a/404.html b/404.html index cbebc21..4eed065 100644 --- a/404.html +++ b/404.html @@ -36,7 +36,7 @@ pharmOncoX - 1.5.5 + 1.5.6 diff --git a/CODE_OF_CONDUCT.html b/CODE_OF_CONDUCT.html index b94ee77..89510b5 100644 --- a/CODE_OF_CONDUCT.html +++ b/CODE_OF_CONDUCT.html @@ -15,7 +15,7 @@ pharmOncoX - 1.5.5 + 1.5.6 diff --git a/LICENSE-text.html b/LICENSE-text.html index 40cf276..08ed787 100644 --- a/LICENSE-text.html +++ b/LICENSE-text.html @@ -15,7 +15,7 @@ pharmOncoX - 1.5.5 + 1.5.6 diff --git a/articles/index.html b/articles/index.html index 17970e5..f532b52 100644 --- a/articles/index.html +++ b/articles/index.html @@ -15,7 +15,7 @@ pharmOncoX - 1.5.5 + 1.5.6 diff --git a/articles/pharmOncoX.html b/articles/pharmOncoX.html index 2b48300..98df089 100644 --- a/articles/pharmOncoX.html +++ b/articles/pharmOncoX.html @@ -38,7 +38,7 @@ pharmOncoX - 1.5.5 + 1.5.6 @@ -109,13 +109,13 @@ Installation#> Downloading GitHub repo sigven/pharmOncoX@HEAD #> #> ── R CMD build ───────────────────────────────────────────────────────────────── -#> * checking for file ‘/tmp/RtmpHGxjPN/remotes18b659a5bc0d/sigven-pharmOncoX-c62cfbd/DESCRIPTION’ ... OK +#> * checking for file ‘/tmp/RtmpsbEbNc/remotes18c6def612b/sigven-pharmOncoX-808bd39/DESCRIPTION’ ... OK #> * preparing ‘pharmOncoX’: #> * checking DESCRIPTION meta-information ... OK #> * checking for LF line-endings in source and make files and shell scripts #> * checking for empty or unneeded directories #> Omitted ‘LazyData’ from DESCRIPTION -#> * building ‘pharmOncoX_1.5.5.tar.gz’ +#> * building ‘pharmOncoX_1.5.6.tar.gz’ #> Installing package into '/home/runner/work/_temp/Library' #> (as 'lib' is unspecified) @@ -164,24 +164,24 @@ Get BRAF-targeted d treatment_category = c("targeted_therapy_classified", "targeted_therapy_unclassified"), drug_target = c('BRAF')) -#> INFO [2024-01-30 13:46:32] Reading from cache_dir = '/tmp/RtmpHGxjPN', argument force_download = F -#> INFO [2024-01-30 13:46:32] Object 'drug_map_name' sucessfully loaded -#> INFO [2024-01-30 13:46:32] Retrieved n = 31302 records -#> INFO [2024-01-30 13:46:33] Reading from cache_dir = '/tmp/RtmpHGxjPN', argument force_download = F -#> INFO [2024-01-30 13:46:33] Object 'drug_map_alias' sucessfully loaded -#> INFO [2024-01-30 13:46:33] Retrieved n = 677250 records -#> INFO [2024-01-30 13:46:33] Reading from cache_dir = '/tmp/RtmpHGxjPN', argument force_download = F -#> INFO [2024-01-30 13:46:33] Object 'drug_map_basic' sucessfully loaded -#> INFO [2024-01-30 13:46:33] Retrieved n = 31337 records -#> INFO [2024-01-30 13:46:33] Reading from cache_dir = '/tmp/RtmpHGxjPN', argument force_download = F -#> INFO [2024-01-30 13:46:33] Object 'drug_map_target' sucessfully loaded -#> INFO [2024-01-30 13:46:33] Retrieved n = 39211 records -#> INFO [2024-01-30 13:46:33] Reading from cache_dir = '/tmp/RtmpHGxjPN', argument force_download = F -#> INFO [2024-01-30 13:46:33] Object 'drug_map_indication' sucessfully loaded -#> INFO [2024-01-30 13:46:33] Retrieved n = 64079 records -#> INFO [2024-01-30 13:46:36] Record set satisfying user-defined criteria: n = 296 -#> INFO [2024-01-30 13:46:36] Collapsing record set - providing output on a 'per_drug_target_indication' resolution -#> INFO [2024-01-30 13:46:36] Final record set: n = 254 records +#> INFO [2024-01-31 09:52:38] Reading from cache_dir = '/tmp/RtmpsbEbNc', argument force_download = F +#> INFO [2024-01-31 09:52:38] Object 'drug_map_name' sucessfully loaded +#> INFO [2024-01-31 09:52:38] Retrieved n = 31302 records +#> INFO [2024-01-31 09:52:38] Reading from cache_dir = '/tmp/RtmpsbEbNc', argument force_download = F +#> INFO [2024-01-31 09:52:38] Object 'drug_map_alias' sucessfully loaded +#> INFO [2024-01-31 09:52:38] Retrieved n = 677250 records +#> INFO [2024-01-31 09:52:38] Reading from cache_dir = '/tmp/RtmpsbEbNc', argument force_download = F +#> INFO [2024-01-31 09:52:38] Object 'drug_map_basic' sucessfully loaded +#> INFO [2024-01-31 09:52:38] Retrieved n = 31337 records +#> INFO [2024-01-31 09:52:38] Reading from cache_dir = '/tmp/RtmpsbEbNc', argument force_download = F +#> INFO [2024-01-31 09:52:38] Object 'drug_map_target' sucessfully loaded +#> INFO [2024-01-31 09:52:38] Retrieved n = 39211 records +#> INFO [2024-01-31 09:52:39] Reading from cache_dir = '/tmp/RtmpsbEbNc', argument force_download = F +#> INFO [2024-01-31 09:52:39] Object 'drug_map_indication' sucessfully loaded +#> INFO [2024-01-31 09:52:39] Retrieved n = 64079 records +#> INFO [2024-01-31 09:52:41] Record set satisfying user-defined criteria: n = 296 +#> INFO [2024-01-31 09:52:41] Collapsing record set - providing output on a 'per_drug_target_indication' resolution +#> INFO [2024-01-31 09:52:41] Final record set: n = 254 records ## Number of drug records nrow(drugs$records) @@ -242,8 +242,8 @@ Get RAS-targeted drugs, lis dom = "Bfrtip") ) - - + + Get MEK inhibitors, list per drug only @@ -278,8 +278,8 @@ Get MEK inhibitors, list per drug dom = "Bfrtip") ) - - + + Get immune checkpoint inhibitors, list per drug target @@ -326,8 +326,8 @@ Get immune checkp dom = "Bfrtip") ) - - + + Get immune checkpoint inhibitors indicated for lung cancer @@ -375,8 +375,8 @@ = "Bfrtip") ) - - + + Get antimetabolite drugs @@ -387,24 +387,24 @@ Get antimetabolite drugs cache_dir = cache_dir, treatment_category = c("chemo_therapy_classified"), output_resolution = "drug") -#> INFO [2024-01-30 13:46:57] Reading from cache_dir = '/tmp/RtmpHGxjPN', argument force_download = F -#> INFO [2024-01-30 13:46:57] Object 'drug_map_name' sucessfully loaded -#> INFO [2024-01-30 13:46:57] Retrieved n = 31302 records -#> INFO [2024-01-30 13:46:57] Reading from cache_dir = '/tmp/RtmpHGxjPN', argument force_download = F -#> INFO [2024-01-30 13:46:57] Object 'drug_map_alias' sucessfully loaded -#> INFO [2024-01-30 13:46:57] Retrieved n = 677250 records -#> INFO [2024-01-30 13:46:57] Reading from cache_dir = '/tmp/RtmpHGxjPN', argument force_download = F -#> INFO [2024-01-30 13:46:57] Object 'drug_map_basic' sucessfully loaded -#> INFO [2024-01-30 13:46:57] Retrieved n = 31337 records -#> INFO [2024-01-30 13:46:57] Reading from cache_dir = '/tmp/RtmpHGxjPN', argument force_download = F -#> INFO [2024-01-30 13:46:57] Object 'drug_map_target' sucessfully loaded -#> INFO [2024-01-30 13:46:57] Retrieved n = 39211 records -#> INFO [2024-01-30 13:46:57] Reading from cache_dir = '/tmp/RtmpHGxjPN', argument force_download = F -#> INFO [2024-01-30 13:46:57] Object 'drug_map_indication' sucessfully loaded -#> INFO [2024-01-30 13:46:57] Retrieved n = 64079 records -#> INFO [2024-01-30 13:47:00] Record set satisfying user-defined criteria: n = 16409 -#> INFO [2024-01-30 13:47:00] Collapsing record set - providing output on a 'per_drug' resolution -#> INFO [2024-01-30 13:47:00] Final record set: n = 146 records +#> INFO [2024-01-31 09:53:05] Reading from cache_dir = '/tmp/RtmpsbEbNc', argument force_download = F +#> INFO [2024-01-31 09:53:05] Object 'drug_map_name' sucessfully loaded +#> INFO [2024-01-31 09:53:05] Retrieved n = 31302 records +#> INFO [2024-01-31 09:53:05] Reading from cache_dir = '/tmp/RtmpsbEbNc', argument force_download = F +#> INFO [2024-01-31 09:53:05] Object 'drug_map_alias' sucessfully loaded +#> INFO [2024-01-31 09:53:05] Retrieved n = 677250 records +#> INFO [2024-01-31 09:53:05] Reading from cache_dir = '/tmp/RtmpsbEbNc', argument force_download = F +#> INFO [2024-01-31 09:53:05] Object 'drug_map_basic' sucessfully loaded +#> INFO [2024-01-31 09:53:05] Retrieved n = 31337 records +#> INFO [2024-01-31 09:53:05] Reading from cache_dir = '/tmp/RtmpsbEbNc', argument force_download = F +#> INFO [2024-01-31 09:53:05] Object 'drug_map_target' sucessfully loaded +#> INFO [2024-01-31 09:53:05] Retrieved n = 39211 records +#> INFO [2024-01-31 09:53:05] Reading from cache_dir = '/tmp/RtmpsbEbNc', argument force_download = F +#> INFO [2024-01-31 09:53:05] Object 'drug_map_indication' sucessfully loaded +#> INFO [2024-01-31 09:53:05] Retrieved n = 64079 records +#> INFO [2024-01-31 09:53:08] Record set satisfying user-defined criteria: n = 16409 +#> INFO [2024-01-31 09:53:08] Collapsing record set - providing output on a 'per_drug' resolution +#> INFO [2024-01-31 09:53:08] Final record set: n = 146 records drugs$records <- drugs$records |> dplyr::filter( @@ -432,8 +432,8 @@ Get antimetabolite drugs dom = "Bfrtip") ) - - + + Get taxanes @@ -444,24 +444,24 @@ Get taxanes= cache_dir, treatment_category = "chemo_therapy_classified", output_resolution = "drug") -#> INFO [2024-01-30 13:47:00] Reading from cache_dir = '/tmp/RtmpHGxjPN', argument force_download = F -#> INFO [2024-01-30 13:47:00] Object 'drug_map_name' sucessfully loaded -#> INFO [2024-01-30 13:47:00] Retrieved n = 31302 records -#> INFO [2024-01-30 13:47:01] Reading from cache_dir = '/tmp/RtmpHGxjPN', argument force_download = F -#> INFO [2024-01-30 13:47:01] Object 'drug_map_alias' sucessfully loaded -#> INFO [2024-01-30 13:47:01] Retrieved n = 677250 records -#> INFO [2024-01-30 13:47:01] Reading from cache_dir = '/tmp/RtmpHGxjPN', argument force_download = F -#> INFO [2024-01-30 13:47:01] Object 'drug_map_basic' sucessfully loaded -#> INFO [2024-01-30 13:47:01] Retrieved n = 31337 records -#> INFO [2024-01-30 13:47:01] Reading from cache_dir = '/tmp/RtmpHGxjPN', argument force_download = F -#> INFO [2024-01-30 13:47:01] Object 'drug_map_target' sucessfully loaded -#> INFO [2024-01-30 13:47:01] Retrieved n = 39211 records -#> INFO [2024-01-30 13:47:01] Reading from cache_dir = '/tmp/RtmpHGxjPN', argument force_download = F -#> INFO [2024-01-30 13:47:01] Object 'drug_map_indication' sucessfully loaded -#> INFO [2024-01-30 13:47:01] Retrieved n = 64079 records -#> INFO [2024-01-30 13:47:04] Record set satisfying user-defined criteria: n = 16409 -#> INFO [2024-01-30 13:47:04] Collapsing record set - providing output on a 'per_drug' resolution -#> INFO [2024-01-30 13:47:04] Final record set: n = 146 records +#> INFO [2024-01-31 09:53:09] Reading from cache_dir = '/tmp/RtmpsbEbNc', argument force_download = F +#> INFO [2024-01-31 09:53:09] Object 'drug_map_name' sucessfully loaded +#> INFO [2024-01-31 09:53:09] Retrieved n = 31302 records +#> INFO [2024-01-31 09:53:09] Reading from cache_dir = '/tmp/RtmpsbEbNc', argument force_download = F +#> INFO [2024-01-31 09:53:09] Object 'drug_map_alias' sucessfully loaded +#> INFO [2024-01-31 09:53:09] Retrieved n = 677250 records +#> INFO [2024-01-31 09:53:09] Reading from cache_dir = '/tmp/RtmpsbEbNc', argument force_download = F +#> INFO [2024-01-31 09:53:09] Object 'drug_map_basic' sucessfully loaded +#> INFO [2024-01-31 09:53:09] Retrieved n = 31337 records +#> INFO [2024-01-31 09:53:09] Reading from cache_dir = '/tmp/RtmpsbEbNc', argument force_download = F +#> INFO [2024-01-31 09:53:09] Object 'drug_map_target' sucessfully loaded +#> INFO [2024-01-31 09:53:09] Retrieved n = 39211 records +#> INFO [2024-01-31 09:53:09] Reading from cache_dir = '/tmp/RtmpsbEbNc', argument force_download = F +#> INFO [2024-01-31 09:53:09] Object 'drug_map_indication' sucessfully loaded +#> INFO [2024-01-31 09:53:09] Retrieved n = 64079 records +#> INFO [2024-01-31 09:53:12] Record set satisfying user-defined criteria: n = 16409 +#> INFO [2024-01-31 09:53:12] Collapsing record set - providing output on a 'per_drug' resolution +#> INFO [2024-01-31 09:53:12] Final record set: n = 146 records drugs$records <- drugs$records |> dplyr::filter( @@ -488,8 +488,8 @@ Get taxanes= "Bfrtip") ) - - + + Get platinum compounds @@ -500,24 +500,24 @@ Get platinum compounds cache_dir = cache_dir, treatment_category = "chemo_therapy_classified", output_resolution = "drug") -#> INFO [2024-01-30 13:47:04] Reading from cache_dir = '/tmp/RtmpHGxjPN', argument force_download = F -#> INFO [2024-01-30 13:47:04] Object 'drug_map_name' sucessfully loaded -#> INFO [2024-01-30 13:47:04] Retrieved n = 31302 records -#> INFO [2024-01-30 13:47:04] Reading from cache_dir = '/tmp/RtmpHGxjPN', argument force_download = F -#> INFO [2024-01-30 13:47:04] Object 'drug_map_alias' sucessfully loaded -#> INFO [2024-01-30 13:47:04] Retrieved n = 677250 records -#> INFO [2024-01-30 13:47:04] Reading from cache_dir = '/tmp/RtmpHGxjPN', argument force_download = F -#> INFO [2024-01-30 13:47:04] Object 'drug_map_basic' sucessfully loaded -#> INFO [2024-01-30 13:47:04] Retrieved n = 31337 records -#> INFO [2024-01-30 13:47:04] Reading from cache_dir = '/tmp/RtmpHGxjPN', argument force_download = F -#> INFO [2024-01-30 13:47:05] Object 'drug_map_target' sucessfully loaded -#> INFO [2024-01-30 13:47:05] Retrieved n = 39211 records -#> INFO [2024-01-30 13:47:05] Reading from cache_dir = '/tmp/RtmpHGxjPN', argument force_download = F -#> INFO [2024-01-30 13:47:05] Object 'drug_map_indication' sucessfully loaded -#> INFO [2024-01-30 13:47:05] Retrieved n = 64079 records -#> INFO [2024-01-30 13:47:07] Record set satisfying user-defined criteria: n = 16409 -#> INFO [2024-01-30 13:47:07] Collapsing record set - providing output on a 'per_drug' resolution -#> INFO [2024-01-30 13:47:07] Final record set: n = 146 records +#> INFO [2024-01-31 09:53:13] Reading from cache_dir = '/tmp/RtmpsbEbNc', argument force_download = F +#> INFO [2024-01-31 09:53:13] Object 'drug_map_name' sucessfully loaded +#> INFO [2024-01-31 09:53:13] Retrieved n = 31302 records +#> INFO [2024-01-31 09:53:13] Reading from cache_dir = '/tmp/RtmpsbEbNc', argument force_download = F +#> INFO [2024-01-31 09:53:13] Object 'drug_map_alias' sucessfully loaded +#> INFO [2024-01-31 09:53:13] Retrieved n = 677250 records +#> INFO [2024-01-31 09:53:13] Reading from cache_dir = '/tmp/RtmpsbEbNc', argument force_download = F +#> INFO [2024-01-31 09:53:13] Object 'drug_map_basic' sucessfully loaded +#> INFO [2024-01-31 09:53:13] Retrieved n = 31337 records +#> INFO [2024-01-31 09:53:13] Reading from cache_dir = '/tmp/RtmpsbEbNc', argument force_download = F +#> INFO [2024-01-31 09:53:13] Object 'drug_map_target' sucessfully loaded +#> INFO [2024-01-31 09:53:13] Retrieved n = 39211 records +#> INFO [2024-01-31 09:53:13] Reading from cache_dir = '/tmp/RtmpsbEbNc', argument force_download = F +#> INFO [2024-01-31 09:53:13] Object 'drug_map_indication' sucessfully loaded +#> INFO [2024-01-31 09:53:13] Retrieved n = 64079 records +#> INFO [2024-01-31 09:53:16] Record set satisfying user-defined criteria: n = 16409 +#> INFO [2024-01-31 09:53:16] Collapsing record set - providing output on a 'per_drug' resolution +#> INFO [2024-01-31 09:53:16] Final record set: n = 146 records drugs$records <- drugs$records |> dplyr::filter( @@ -544,8 +544,8 @@ Get platinum compounds dom = "Bfrtip") ) - - + + @@ -564,10 +564,10 @@ R biomarkers <- get_biomarkers( cache_dir = cache_dir) -#> INFO [2024-01-30 13:47:07] Downloading remote dataset from Google Drive to cache_dir -#> INFO [2024-01-30 13:47:11] Reading from cache_dir = ' (/tmp/RtmpHGxjPN'), argument force_download = F -#> INFO [2024-01-30 13:47:11] Object 'biomarkers' sucessfully loaded -#> INFO [2024-01-30 13:47:11] md5 checksum is valid: d3a942cfc0a999ad2d33610379ebd08b +#> INFO [2024-01-31 09:53:17] Downloading remote dataset from Google Drive to cache_dir +#> INFO [2024-01-31 09:53:20] Reading from cache_dir = ' (/tmp/RtmpsbEbNc'), argument force_download = F +#> INFO [2024-01-31 09:53:20] Object 'biomarkers' sucessfully loaded +#> INFO [2024-01-31 09:53:20] md5 checksum is valid: 98fcfe1b54c2b393112c0be81e58fc9e brca1_biomarkers <- list() for(source in c('civic','cgi')){ @@ -617,8 +617,8 @@ R dom = "Bfrtip") ) - - + + @@ -649,7 +649,7 @@ Session Info#> [1] stats graphics grDevices utils datasets methods base #> #> other attached packages: -#> [1] pharmOncoX_1.5.5 +#> [1] pharmOncoX_1.5.6 #> #> loaded via a namespace (and not attached): #> [1] sass_0.4.8 utf8_1.2.4 generics_0.1.3 stringi_1.8.3 diff --git a/authors.html b/authors.html index 52e7f90..4a37899 100644 --- a/authors.html +++ b/authors.html @@ -15,7 +15,7 @@ pharmOncoX - 1.5.5 + 1.5.6 @@ -64,12 +64,12 @@ Authors Citation Source: inst/CITATION - Nakken S. (2023) pharmOncoX: Targeted and non-targeted anti-cancer drugs and drug regimens. R package version 1.5.5. (https://github.com/sigven/pharmOncoX) + Nakken S. (2023) pharmOncoX: Targeted and non-targeted anti-cancer drugs and drug regimens. R package version 1.5.6. (https://github.com/sigven/pharmOncoX) @Manual{, title = {pharmOncoX: Targeted and non-targeted anti-cancer drugs and drug regimens}, author = {Sigve Nakken}, year = {2023}, - note = {R package version 1.5.5}, + note = {R package version 1.5.6}, url = {https://github.com/sigven/pharmOncoX}, } diff --git a/index.html b/index.html index 6d5894c..e1430ef 100644 --- a/index.html +++ b/index.html @@ -54,7 +54,7 @@ pharmOncoX - 1.5.5 + 1.5.6 diff --git a/news/index.html b/news/index.html index 7b6b343..df9b786 100644 --- a/news/index.html +++ b/news/index.html @@ -15,7 +15,7 @@ pharmOncoX - 1.5.5 + 1.5.6 @@ -53,12 +53,13 @@ -Version 1.5.5 (January 30th 2024) +Version 1.5.6 (January 31st 2024) Refine possible values in treatment_category argument to get_drugs() function Fix anti-androgen classification Fixed bug in alias type notation for copy numbers and expression biomarkers Filter noise and rank output in helper function get_targeted_drugs +Include variant primary name in biomarker variants Version 1.5.0 (January 25th 2024) diff --git a/pkgdown.yml b/pkgdown.yml index f52db83..b3fe110 100644 --- a/pkgdown.yml +++ b/pkgdown.yml @@ -3,7 +3,7 @@ pkgdown: 2.0.7 pkgdown_sha: ~ articles: pharmOncoX: pharmOncoX.html -last_built: 2024-01-30T13:45Z +last_built: 2024-01-31T09:52Z urls: reference: https://sigven.github.io/pharmOncoX/reference article: https://sigven.github.io/pharmOncoX/articles diff --git a/reference/get_biomarkers.html b/reference/get_biomarkers.html index 69a6f90..4ec3835 100644 --- a/reference/get_biomarkers.html +++ b/reference/get_biomarkers.html @@ -31,7 +31,7 @@ pharmOncoX - 1.5.5 + 1.5.6 diff --git a/reference/get_drug_records.html b/reference/get_drug_records.html index 6673b24..651eaec 100644 --- a/reference/get_drug_records.html +++ b/reference/get_drug_records.html @@ -15,7 +15,7 @@ pharmOncoX - 1.5.5 + 1.5.6 diff --git a/reference/get_drugs.html b/reference/get_drugs.html index 984e107..96ed833 100644 --- a/reference/get_drugs.html +++ b/reference/get_drugs.html @@ -27,7 +27,7 @@ pharmOncoX - 1.5.5 + 1.5.6 diff --git a/reference/get_targeted_drugs.html b/reference/get_targeted_drugs.html index f0f1bd4..ceca8ad 100644 --- a/reference/get_targeted_drugs.html +++ b/reference/get_targeted_drugs.html @@ -15,7 +15,7 @@ pharmOncoX - 1.5.5 + 1.5.6 diff --git a/reference/index.html b/reference/index.html index d268561..a796930 100644 --- a/reference/index.html +++ b/reference/index.html @@ -15,7 +15,7 @@ pharmOncoX - 1.5.5 + 1.5.6 diff --git a/reference/tidyeval.html b/reference/tidyeval.html index 70f11c7..984ccf2 100644 --- a/reference/tidyeval.html +++ b/reference/tidyeval.html @@ -15,7 +15,7 @@ pharmOncoX - 1.5.5 + 1.5.6 diff --git a/search.json b/search.json index 1012160..e8178c9 100644 --- a/search.json +++ b/search.json @@ -1 +1 @@ -[{"path":[]},{"path":"https://sigven.github.io/pharmOncoX/CODE_OF_CONDUCT.html","id":"our-pledge","dir":"","previous_headings":"","what":"Our Pledge","title":"Contributor Covenant Code of Conduct","text":"members, contributors, leaders pledge make participation community harassment-free experience everyone, regardless age, body size, visible invisible disability, ethnicity, sex characteristics, gender identity expression, level experience, education, socio-economic status, nationality, personal appearance, race, religion, sexual identity orientation. pledge act interact ways contribute open, welcoming, diverse, inclusive, healthy community.","code":""},{"path":"https://sigven.github.io/pharmOncoX/CODE_OF_CONDUCT.html","id":"our-standards","dir":"","previous_headings":"","what":"Our Standards","title":"Contributor Covenant Code of Conduct","text":"Examples behavior contributes positive environment community include: Demonstrating empathy kindness toward people respectful differing opinions, viewpoints, experiences Giving gracefully accepting constructive feedback Accepting responsibility apologizing affected mistakes, learning experience Focusing best just us individuals, overall community Examples unacceptable behavior include: use sexualized language imagery, sexual attention advances kind Trolling, insulting derogatory comments, personal political attacks Public private harassment Publishing others’ private information, physical email address, without explicit permission conduct reasonably considered inappropriate professional setting","code":""},{"path":"https://sigven.github.io/pharmOncoX/CODE_OF_CONDUCT.html","id":"enforcement-responsibilities","dir":"","previous_headings":"","what":"Enforcement Responsibilities","title":"Contributor Covenant Code of Conduct","text":"Community leaders responsible clarifying enforcing standards acceptable behavior take appropriate fair corrective action response behavior deem inappropriate, threatening, offensive, harmful. Community leaders right responsibility remove, edit, reject comments, commits, code, wiki edits, issues, contributions aligned Code Conduct, communicate reasons moderation decisions appropriate.","code":""},{"path":"https://sigven.github.io/pharmOncoX/CODE_OF_CONDUCT.html","id":"scope","dir":"","previous_headings":"","what":"Scope","title":"Contributor Covenant Code of Conduct","text":"Code Conduct applies within community spaces, also applies individual officially representing community public spaces. Examples representing community include using official e-mail address, posting via official social media account, acting appointed representative online offline event.","code":""},{"path":"https://sigven.github.io/pharmOncoX/CODE_OF_CONDUCT.html","id":"enforcement","dir":"","previous_headings":"","what":"Enforcement","title":"Contributor Covenant Code of Conduct","text":"Instances abusive, harassing, otherwise unacceptable behavior may reported community leaders responsible enforcement [INSERT CONTACT METHOD]. complaints reviewed investigated promptly fairly. community leaders obligated respect privacy security reporter incident.","code":""},{"path":"https://sigven.github.io/pharmOncoX/CODE_OF_CONDUCT.html","id":"enforcement-guidelines","dir":"","previous_headings":"","what":"Enforcement Guidelines","title":"Contributor Covenant Code of Conduct","text":"Community leaders follow Community Impact Guidelines determining consequences action deem violation Code Conduct:","code":""},{"path":"https://sigven.github.io/pharmOncoX/CODE_OF_CONDUCT.html","id":"id_1-correction","dir":"","previous_headings":"Enforcement Guidelines","what":"1. Correction","title":"Contributor Covenant Code of Conduct","text":"Community Impact: Use inappropriate language behavior deemed unprofessional unwelcome community. Consequence: private, written warning community leaders, providing clarity around nature violation explanation behavior inappropriate. public apology may requested.","code":""},{"path":"https://sigven.github.io/pharmOncoX/CODE_OF_CONDUCT.html","id":"id_2-warning","dir":"","previous_headings":"Enforcement Guidelines","what":"2. Warning","title":"Contributor Covenant Code of Conduct","text":"Community Impact: violation single incident series actions. Consequence: warning consequences continued behavior. interaction people involved, including unsolicited interaction enforcing Code Conduct, specified period time. includes avoiding interactions community spaces well external channels like social media. Violating terms may lead temporary permanent ban.","code":""},{"path":"https://sigven.github.io/pharmOncoX/CODE_OF_CONDUCT.html","id":"id_3-temporary-ban","dir":"","previous_headings":"Enforcement Guidelines","what":"3. Temporary Ban","title":"Contributor Covenant Code of Conduct","text":"Community Impact: serious violation community standards, including sustained inappropriate behavior. Consequence: temporary ban sort interaction public communication community specified period time. public private interaction people involved, including unsolicited interaction enforcing Code Conduct, allowed period. Violating terms may lead permanent ban.","code":""},{"path":"https://sigven.github.io/pharmOncoX/CODE_OF_CONDUCT.html","id":"id_4-permanent-ban","dir":"","previous_headings":"Enforcement Guidelines","what":"4. Permanent Ban","title":"Contributor Covenant Code of Conduct","text":"Community Impact: Demonstrating pattern violation community standards, including sustained inappropriate behavior, harassment individual, aggression toward disparagement classes individuals. Consequence: permanent ban sort public interaction within community.","code":""},{"path":"https://sigven.github.io/pharmOncoX/CODE_OF_CONDUCT.html","id":"attribution","dir":"","previous_headings":"","what":"Attribution","title":"Contributor Covenant Code of Conduct","text":"Code Conduct adapted Contributor Covenant, version 2.0, available https://www.contributor-covenant.org/version/2/0/ code_of_conduct.html. Community Impact Guidelines inspired Mozilla’s code conduct enforcement ladder. answers common questions code conduct, see FAQ https://www.contributor-covenant.org/faq. Translations available https:// www.contributor-covenant.org/translations.","code":""},{"path":"https://sigven.github.io/pharmOncoX/articles/pharmOncoX.html","id":"installation","dir":"Articles","previous_headings":"","what":"Installation","title":"Getting started","text":"","code":"if (!(\"remotes\" %in% installed.packages())) { install.packages(\"remotes\") } remotes::install_github('sigven/pharmOncoX') #> Using github PAT from envvar GITHUB_PAT #> Downloading GitHub repo sigven/pharmOncoX@HEAD #> #> ── R CMD build ───────────────────────────────────────────────────────────────── #> * checking for file ‘/tmp/RtmpHGxjPN/remotes18b659a5bc0d/sigven-pharmOncoX-c62cfbd/DESCRIPTION’ ... OK #> * preparing ‘pharmOncoX’: #> * checking DESCRIPTION meta-information ... OK #> * checking for LF line-endings in source and make files and shell scripts #> * checking for empty or unneeded directories #> Omitted ‘LazyData’ from DESCRIPTION #> * building ‘pharmOncoX_1.5.5.tar.gz’ #> Installing package into '/home/runner/work/_temp/Library' #> (as 'lib' is unspecified) library(pharmOncoX) cache_dir <- tempdir()"},{"path":[]},{"path":"https://sigven.github.io/pharmOncoX/articles/pharmOncoX.html","id":"targeted-agents","dir":"Articles","previous_headings":"Cancer drug classifications","what":"Targeted agents","title":"Getting started","text":"Plotted key statistics respect drug classification numbers targeted chemotherapy agents found pharmOncoX. Existing drug classifications retrieved ATC, extended manual addition/curation, also establishment multiple novel levels ATC tree, particularly targeted therapies. Note drugs indicated cancer conditions (harvested Open Targets platform) considered numbers plotted .","code":"p_targeted_classifications"},{"path":"https://sigven.github.io/pharmOncoX/articles/pharmOncoX.html","id":"chemotherapy-agents","dir":"Articles","previous_headings":"Cancer drug classifications","what":"Chemotherapy agents","title":"Getting started","text":"","code":"p_chemo_classifications"},{"path":[]},{"path":"https://sigven.github.io/pharmOncoX/articles/pharmOncoX.html","id":"get-braf-targeted-drugs-list-records-per-indication","dir":"Articles","previous_headings":"Retrieval of drugs - examples","what":"Get BRAF-targeted drugs, list records per indication","title":"Getting started","text":"","code":"drugs <- get_drugs( cache_dir = cache_dir, treatment_category = c(\"targeted_therapy_classified\", \"targeted_therapy_unclassified\"), drug_target = c('BRAF')) #> INFO [2024-01-30 13:46:32] Reading from cache_dir = '/tmp/RtmpHGxjPN', argument force_download = F #> INFO [2024-01-30 13:46:32] Object 'drug_map_name' sucessfully loaded #> INFO [2024-01-30 13:46:32] Retrieved n = 31302 records #> INFO [2024-01-30 13:46:33] Reading from cache_dir = '/tmp/RtmpHGxjPN', argument force_download = F #> INFO [2024-01-30 13:46:33] Object 'drug_map_alias' sucessfully loaded #> INFO [2024-01-30 13:46:33] Retrieved n = 677250 records #> INFO [2024-01-30 13:46:33] Reading from cache_dir = '/tmp/RtmpHGxjPN', argument force_download = F #> INFO [2024-01-30 13:46:33] Object 'drug_map_basic' sucessfully loaded #> INFO [2024-01-30 13:46:33] Retrieved n = 31337 records #> INFO [2024-01-30 13:46:33] Reading from cache_dir = '/tmp/RtmpHGxjPN', argument force_download = F #> INFO [2024-01-30 13:46:33] Object 'drug_map_target' sucessfully loaded #> INFO [2024-01-30 13:46:33] Retrieved n = 39211 records #> INFO [2024-01-30 13:46:33] Reading from cache_dir = '/tmp/RtmpHGxjPN', argument force_download = F #> INFO [2024-01-30 13:46:33] Object 'drug_map_indication' sucessfully loaded #> INFO [2024-01-30 13:46:33] Retrieved n = 64079 records #> INFO [2024-01-30 13:46:36] Record set satisfying user-defined criteria: n = 296 #> INFO [2024-01-30 13:46:36] Collapsing record set - providing output on a 'per_drug_target_indication' resolution #> INFO [2024-01-30 13:46:36] Final record set: n = 254 records ## Number of drug records nrow(drugs$records) #> [1] 254 ## Column names of drug records colnames(drugs$records) #> [1] \"drug_id\" \"drug_name\" #> [3] \"drug_type\" \"molecule_chembl_id\" #> [5] \"drug_action_type\" \"drug_alias\" #> [7] \"nci_concept_definition\" \"opentargets\" #> [9] \"drug_cancer_relevance\" \"inhibition_moa\" #> [11] \"is_salt\" \"is_adc\" #> [13] \"drug_blackbox_warning\" \"nci_t\" #> [15] \"target_symbol\" \"target_entrezgene\" #> [17] \"target_genename\" \"target_ensembl_gene_id\" #> [19] \"target_type\" \"drug_max_phase_indication\" #> [21] \"drug_approved_indication\" \"drug_frac_cancer_indications\" #> [23] \"drug_approved_noncancer\" \"drug_n_indications\" #> [25] \"drug_year_first_approval\" \"drug_max_ct_phase\" #> [27] \"disease_efo_id\" \"disease_efo_label\" #> [29] \"primary_site\" \"drug_clinical_id\" #> [31] \"drug_clinical_source\" \"atc_code_level1\" #> [33] \"atc_level1\" \"atc_code_level2\" #> [35] \"atc_level2\" \"atc_code_level3\" #> [37] \"atc_level3\" \"atc_treatment_category\""},{"path":"https://sigven.github.io/pharmOncoX/articles/pharmOncoX.html","id":"get-ras-targeted-drugs-list-per-drug-target","dir":"Articles","previous_headings":"Retrieval of drugs - examples","what":"Get RAS-targeted drugs, list per drug target","title":"Getting started","text":"","code":"drugs <- get_drugs( cache_dir = cache_dir, treatment_category = c(\"targeted_therapy_classified\"), drug_action_inhibition = T, output_resolution = \"drug2target\")$records |> dplyr::filter(atc_level3 == \"RAS inhibitors\") drugs <- drugs |> dplyr::select( -c(\"drug_alias\", \"disease_main_group\", \"drug_clinical_id\")) |> dplyr::mutate( disease_indication = stringr::str_replace_all( disease_indication, \"\\\\|\",\", \") ) dt_drugtable_ras_inhibitors <- DT::datatable( drugs, escape = FALSE, extensions = c(\"Buttons\", \"Responsive\"), width = \"100%\", options = list( buttons = c(\"csv\", \"excel\"), dom = \"Bfrtip\") )"},{"path":"https://sigven.github.io/pharmOncoX/articles/pharmOncoX.html","id":"get-mek-inhibitors-list-per-drug-only","dir":"Articles","previous_headings":"Retrieval of drugs - examples","what":"Get MEK inhibitors, list per drug only","title":"Getting started","text":"","code":"drugs <- get_drugs( cache_dir = cache_dir, treatment_category = c(\"targeted_therapy_classified\"), drug_action_inhibition = T, drug_source_opentargets = T, output_resolution = \"drug\" )$records |> dplyr::filter(atc_level3 == \"MEK inhibitors\") drugs <- drugs |> dplyr::select( -c(\"drug_alias\", \"disease_main_group\", \"drug_clinical_id\")) |> dplyr::mutate( disease_indication = stringr::str_replace_all( disease_indication, \"\\\\|\",\", \") ) dt_drugtable_mek_inhibitors <- DT::datatable( drugs, escape = FALSE, extensions = c(\"Buttons\", \"Responsive\"), width = \"100%\", options = list( buttons = c(\"csv\", \"excel\"), dom = \"Bfrtip\") )"},{"path":"https://sigven.github.io/pharmOncoX/articles/pharmOncoX.html","id":"get-immune-checkpoint-inhibitors-list-per-drug-target","dir":"Articles","previous_headings":"Retrieval of drugs - examples","what":"Get immune checkpoint inhibitors, list per drug target","title":"Getting started","text":"","code":"drugs <- get_drugs( cache_dir = cache_dir, treatment_category = c(\"targeted_therapy_classified\"), drug_source_opentargets = F, drug_classified_cancer = T, output_resolution = \"drug2target\") drugs$records <- drugs$records |> dplyr::filter( (!is.na(atc_level3) & (atc_level3 == \"PD-1/PDL-1 inhibitors\" | atc_level3 == \"Other immune checkpoint inhibitors\") )) |> dplyr::select( -c(\"drug_alias\", \"disease_main_group\", \"drug_clinical_id\")) |> dplyr::mutate( disease_indication = stringr::str_replace_all( disease_indication, \"\\\\|\",\", \") ) |> dplyr::select( drug_id, drug_name, drug_type, target_symbol, target_genename, dplyr::everything() ) dt_drugtable_ici <- DT::datatable( drugs$records, escape = FALSE, extensions = c(\"Buttons\", \"Responsive\"), width = \"100%\", options = list( buttons = c(\"csv\", \"excel\"), dom = \"Bfrtip\") )"},{"path":"https://sigven.github.io/pharmOncoX/articles/pharmOncoX.html","id":"get-immune-checkpoint-inhibitors-indicated-for-lung-cancer-conditions-list-per-drug-target-entry","dir":"Articles","previous_headings":"Retrieval of drugs - examples","what":"Get immune checkpoint inhibitors indicated for lung cancer conditions, list per drug-target entry","title":"Getting started","text":"","code":"drugs <- get_drugs( cache_dir = cache_dir, output_resolution = \"drug2target\", treatment_category = c(\"targeted_therapy_classified\"), drug_source_opentargets = T, drug_indication_main = \"Lung\") drugs$records <- drugs$records |> dplyr::filter( (!is.na(atc_level3) & (atc_level3 == \"PD-1/PDL-1 inhibitors\" | atc_level3 == \"Other immune checkpoint inhibitors\") )) |> dplyr::select( -c(\"drug_alias\", \"disease_main_group\", \"drug_clinical_id\")) |> dplyr::mutate( disease_indication = stringr::str_replace_all( disease_indication, \"\\\\|\",\", \") ) |> dplyr::select( drug_id, drug_name, drug_type, target_symbol, target_genename, dplyr::everything() ) dt_drugtable_ici_lung <- DT::datatable( drugs$records, escape = FALSE, extensions = c(\"Buttons\", \"Responsive\"), width = \"100%\", options = list( buttons = c(\"csv\", \"excel\"), dom = \"Bfrtip\") )"},{"path":"https://sigven.github.io/pharmOncoX/articles/pharmOncoX.html","id":"get-antimetabolite-drugs","dir":"Articles","previous_headings":"Retrieval of drugs - examples","what":"Get antimetabolite drugs","title":"Getting started","text":"","code":"drugs <- get_drugs( cache_dir = cache_dir, treatment_category = c(\"chemo_therapy_classified\"), output_resolution = \"drug\") #> INFO [2024-01-30 13:46:57] Reading from cache_dir = '/tmp/RtmpHGxjPN', argument force_download = F #> INFO [2024-01-30 13:46:57] Object 'drug_map_name' sucessfully loaded #> INFO [2024-01-30 13:46:57] Retrieved n = 31302 records #> INFO [2024-01-30 13:46:57] Reading from cache_dir = '/tmp/RtmpHGxjPN', argument force_download = F #> INFO [2024-01-30 13:46:57] Object 'drug_map_alias' sucessfully loaded #> INFO [2024-01-30 13:46:57] Retrieved n = 677250 records #> INFO [2024-01-30 13:46:57] Reading from cache_dir = '/tmp/RtmpHGxjPN', argument force_download = F #> INFO [2024-01-30 13:46:57] Object 'drug_map_basic' sucessfully loaded #> INFO [2024-01-30 13:46:57] Retrieved n = 31337 records #> INFO [2024-01-30 13:46:57] Reading from cache_dir = '/tmp/RtmpHGxjPN', argument force_download = F #> INFO [2024-01-30 13:46:57] Object 'drug_map_target' sucessfully loaded #> INFO [2024-01-30 13:46:57] Retrieved n = 39211 records #> INFO [2024-01-30 13:46:57] Reading from cache_dir = '/tmp/RtmpHGxjPN', argument force_download = F #> INFO [2024-01-30 13:46:57] Object 'drug_map_indication' sucessfully loaded #> INFO [2024-01-30 13:46:57] Retrieved n = 64079 records #> INFO [2024-01-30 13:47:00] Record set satisfying user-defined criteria: n = 16409 #> INFO [2024-01-30 13:47:00] Collapsing record set - providing output on a 'per_drug' resolution #> INFO [2024-01-30 13:47:00] Final record set: n = 146 records drugs$records <- drugs$records |> dplyr::filter( !is.na(atc_level2) & stringr::str_detect( atc_level2, \"ANTIMETABOLITES\" ) ) |> dplyr::select( -c(\"drug_alias\", \"disease_main_group\", \"drug_clinical_id\")) |> dplyr::mutate( disease_indication = stringr::str_replace_all( disease_indication, \"\\\\|\",\", \") ) dt_drugtable_metabolites <- DT::datatable( drugs$records, escape = FALSE, extensions = c(\"Buttons\", \"Responsive\"), width = \"100%\", options = list( buttons = c(\"csv\", \"excel\"), dom = \"Bfrtip\") )"},{"path":"https://sigven.github.io/pharmOncoX/articles/pharmOncoX.html","id":"get-taxanes","dir":"Articles","previous_headings":"Retrieval of drugs - examples","what":"Get taxanes","title":"Getting started","text":"","code":"drugs <- get_drugs( cache_dir = cache_dir, treatment_category = \"chemo_therapy_classified\", output_resolution = \"drug\") #> INFO [2024-01-30 13:47:00] Reading from cache_dir = '/tmp/RtmpHGxjPN', argument force_download = F #> INFO [2024-01-30 13:47:00] Object 'drug_map_name' sucessfully loaded #> INFO [2024-01-30 13:47:00] Retrieved n = 31302 records #> INFO [2024-01-30 13:47:01] Reading from cache_dir = '/tmp/RtmpHGxjPN', argument force_download = F #> INFO [2024-01-30 13:47:01] Object 'drug_map_alias' sucessfully loaded #> INFO [2024-01-30 13:47:01] Retrieved n = 677250 records #> INFO [2024-01-30 13:47:01] Reading from cache_dir = '/tmp/RtmpHGxjPN', argument force_download = F #> INFO [2024-01-30 13:47:01] Object 'drug_map_basic' sucessfully loaded #> INFO [2024-01-30 13:47:01] Retrieved n = 31337 records #> INFO [2024-01-30 13:47:01] Reading from cache_dir = '/tmp/RtmpHGxjPN', argument force_download = F #> INFO [2024-01-30 13:47:01] Object 'drug_map_target' sucessfully loaded #> INFO [2024-01-30 13:47:01] Retrieved n = 39211 records #> INFO [2024-01-30 13:47:01] Reading from cache_dir = '/tmp/RtmpHGxjPN', argument force_download = F #> INFO [2024-01-30 13:47:01] Object 'drug_map_indication' sucessfully loaded #> INFO [2024-01-30 13:47:01] Retrieved n = 64079 records #> INFO [2024-01-30 13:47:04] Record set satisfying user-defined criteria: n = 16409 #> INFO [2024-01-30 13:47:04] Collapsing record set - providing output on a 'per_drug' resolution #> INFO [2024-01-30 13:47:04] Final record set: n = 146 records drugs$records <- drugs$records |> dplyr::filter( stringr::str_detect( atc_level3, \"Taxanes\" ) ) |> dplyr::select( -c(\"drug_alias\", \"disease_main_group\", \"drug_clinical_id\")) |> dplyr::mutate( disease_indication = stringr::str_replace_all( disease_indication, \"\\\\|\",\", \") ) dt_drugtable_taxanes <- DT::datatable( drugs$records, escape = FALSE, extensions = c(\"Buttons\", \"Responsive\"), width = \"100%\", options = list( buttons = c(\"csv\", \"excel\"), dom = \"Bfrtip\") )"},{"path":"https://sigven.github.io/pharmOncoX/articles/pharmOncoX.html","id":"get-platinum-compounds","dir":"Articles","previous_headings":"Retrieval of drugs - examples","what":"Get platinum compounds","title":"Getting started","text":"","code":"drugs <- get_drugs( cache_dir = cache_dir, treatment_category = \"chemo_therapy_classified\", output_resolution = \"drug\") #> INFO [2024-01-30 13:47:04] Reading from cache_dir = '/tmp/RtmpHGxjPN', argument force_download = F #> INFO [2024-01-30 13:47:04] Object 'drug_map_name' sucessfully loaded #> INFO [2024-01-30 13:47:04] Retrieved n = 31302 records #> INFO [2024-01-30 13:47:04] Reading from cache_dir = '/tmp/RtmpHGxjPN', argument force_download = F #> INFO [2024-01-30 13:47:04] Object 'drug_map_alias' sucessfully loaded #> INFO [2024-01-30 13:47:04] Retrieved n = 677250 records #> INFO [2024-01-30 13:47:04] Reading from cache_dir = '/tmp/RtmpHGxjPN', argument force_download = F #> INFO [2024-01-30 13:47:04] Object 'drug_map_basic' sucessfully loaded #> INFO [2024-01-30 13:47:04] Retrieved n = 31337 records #> INFO [2024-01-30 13:47:04] Reading from cache_dir = '/tmp/RtmpHGxjPN', argument force_download = F #> INFO [2024-01-30 13:47:05] Object 'drug_map_target' sucessfully loaded #> INFO [2024-01-30 13:47:05] Retrieved n = 39211 records #> INFO [2024-01-30 13:47:05] Reading from cache_dir = '/tmp/RtmpHGxjPN', argument force_download = F #> INFO [2024-01-30 13:47:05] Object 'drug_map_indication' sucessfully loaded #> INFO [2024-01-30 13:47:05] Retrieved n = 64079 records #> INFO [2024-01-30 13:47:07] Record set satisfying user-defined criteria: n = 16409 #> INFO [2024-01-30 13:47:07] Collapsing record set - providing output on a 'per_drug' resolution #> INFO [2024-01-30 13:47:07] Final record set: n = 146 records drugs$records <- drugs$records |> dplyr::filter( stringr::str_detect( atc_level3, \"Platinum compounds\" ) ) |> dplyr::select( -c(\"drug_alias\", \"disease_main_group\", \"drug_clinical_id\")) |> dplyr::mutate( disease_indication = stringr::str_replace_all( disease_indication, \"\\\\|\",\", \") ) dt_drugtable_platins <- DT::datatable( drugs$records, escape = FALSE, extensions = c(\"Buttons\", \"Responsive\"), width = \"100%\", options = list( buttons = c(\"csv\", \"excel\"), dom = \"Bfrtip\") )"},{"path":[]},{"path":"https://sigven.github.io/pharmOncoX/articles/pharmOncoX.html","id":"reported-associations-between-brca12-alterations-and-drug-sensitivity","dir":"Articles","previous_headings":"Retrieval of biomarkers","what":"Reported associations between BRCA1/2 alterations and drug sensitivity","title":"Getting started","text":"Get evidence CIViC CGI cancer drug sensitivity BRCA1/2 alterations (somatically (tumor) inherited/germline)","code":"biomarkers <- get_biomarkers( cache_dir = cache_dir) #> INFO [2024-01-30 13:47:07] Downloading remote dataset from Google Drive to cache_dir #> INFO [2024-01-30 13:47:11] Reading from cache_dir = ' (/tmp/RtmpHGxjPN'), argument force_download = F #> INFO [2024-01-30 13:47:11] Object 'biomarkers' sucessfully loaded #> INFO [2024-01-30 13:47:11] md5 checksum is valid: d3a942cfc0a999ad2d33610379ebd08b brca1_biomarkers <- list() for(source in c('civic','cgi')){ brca1_biomarkers[[source]] <- biomarkers$data[[source]]$variant |> dplyr::filter( !is.na(symbol) & (symbol == \"BRCA1\" | symbol == \"BRCA2\")) |> dplyr::group_by(variant_id, symbol, variant_consequence) |> dplyr::summarise( variant_alias = paste(variant_alias, collapse=\", \"), .groups = \"drop\") |> dplyr::inner_join( biomarkers$data[[source]]$clinical, by = \"variant_id\") |> dplyr::select( variant_id, symbol, variant_consequence, variant_alias, biomarker_source, biomarker_source_datestamp, molecular_profile_name, evidence_id, variant_origin, primary_site, evidence_id, source_id, evidence_url, therapeutic_context, evidence_description, evidence_type, evidence_level, clinical_significance) |> dplyr::distinct() |> dplyr::rename(literature_id = source_id) |> dplyr::filter(evidence_type == \"Predictive\") |> dplyr::select( symbol, primary_site, therapeutic_context, molecular_profile_name, evidence_level, dplyr::everything() ) } brca1_biomarkers_all <- dplyr::bind_rows(brca1_biomarkers[['civic']], brca1_biomarkers[['cgi']]) |> dplyr::arrange(evidence_level) dt_brca1_biomarkers <- DT::datatable( brca1_biomarkers_all, escape = FALSE, extensions = c(\"Buttons\", \"Responsive\"), width = \"100%\", options = list( buttons = c(\"csv\", \"excel\"), dom = \"Bfrtip\") )"},{"path":"https://sigven.github.io/pharmOncoX/articles/pharmOncoX.html","id":"session-info","dir":"Articles","previous_headings":"","what":"Session Info","title":"Getting started","text":"","code":"# set eval = FALSE if you don't want this info (useful for reproducibility) # to appear sessionInfo() #> R version 4.3.2 (2023-10-31) #> Platform: x86_64-pc-linux-gnu (64-bit) #> Running under: Ubuntu 22.04.3 LTS #> #> Matrix products: default #> BLAS: /usr/lib/x86_64-linux-gnu/openblas-pthread/libblas.so.3 #> LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.20.so; LAPACK version 3.10.0 #> #> locale: #> [1] LC_CTYPE=C.UTF-8 LC_NUMERIC=C LC_TIME=C.UTF-8 #> [4] LC_COLLATE=C.UTF-8 LC_MONETARY=C.UTF-8 LC_MESSAGES=C.UTF-8 #> [7] LC_PAPER=C.UTF-8 LC_NAME=C LC_ADDRESS=C #> [10] LC_TELEPHONE=C LC_MEASUREMENT=C.UTF-8 LC_IDENTIFICATION=C #> #> time zone: UTC #> tzcode source: system (glibc) #> #> attached base packages: #> [1] stats graphics grDevices utils datasets methods base #> #> other attached packages: #> [1] pharmOncoX_1.5.5 #> #> loaded via a namespace (and not attached): #> [1] sass_0.4.8 utf8_1.2.4 generics_0.1.3 stringi_1.8.3 #> [5] digest_0.6.34 magrittr_2.0.3 grid_4.3.2 evaluate_0.23 #> [9] fastmap_1.1.1 jsonlite_1.8.8 processx_3.8.3 pkgbuild_1.4.3 #> [13] googledrive_2.1.1 ps_1.7.6 httr_1.4.7 purrr_1.0.2 #> [17] fansi_1.0.6 crosstalk_1.2.1 scales_1.3.0 textshaping_0.3.7 #> [21] jquerylib_0.1.4 cli_3.6.2 rlang_1.1.3 crayon_1.5.2 #> [25] ellipsis_0.3.2 munsell_0.5.0 remotes_2.4.2.1 withr_3.0.0 #> [29] cachem_1.0.8 yaml_2.3.8 tools_4.3.2 gargle_1.5.2 #> [33] memoise_2.0.1 dplyr_1.1.4 colorspace_2.1-0 ggplot2_3.4.4 #> [37] DT_0.31 curl_5.2.0 assertthat_0.2.1 vctrs_0.6.5 #> [41] R6_2.5.1 lifecycle_1.0.4 stringr_1.5.1 htmlwidgets_1.6.4 #> [45] fs_1.6.3 ragg_1.2.7 pkgconfig_2.0.3 desc_1.4.3 #> [49] callr_3.7.3 gtable_0.3.4 pkgdown_2.0.7 bslib_0.6.1 #> [53] pillar_1.9.0 glue_1.7.0 lgr_0.4.4 systemfonts_1.0.5 #> [57] highr_0.10 xfun_0.41 tibble_3.2.1 tidyselect_1.2.0 #> [61] knitr_1.45 farver_2.1.1 htmltools_0.5.7 rmarkdown_2.25 #> [65] compiler_4.3.2"},{"path":[]},{"path":"https://sigven.github.io/pharmOncoX/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Sigve Nakken. Author, maintainer.","code":""},{"path":"https://sigven.github.io/pharmOncoX/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Nakken S. (2023) pharmOncoX: Targeted non-targeted anti-cancer drugs drug regimens. R package version 1.5.5. (https://github.com/sigven/pharmOncoX)","code":"@Manual{, title = {pharmOncoX: Targeted and non-targeted anti-cancer drugs and drug regimens}, author = {Sigve Nakken}, year = {2023}, note = {R package version 1.5.5}, url = {https://github.com/sigven/pharmOncoX}, }"},{"path":"https://sigven.github.io/pharmOncoX/index.html","id":"pharmoncox-","dir":"","previous_headings":"","what":"Molecularly targeted cancer drugs and biomarkers","title":"Molecularly targeted cancer drugs and biomarkers","text":"pharmOncoX provides access targeted non-targeted cancer drugs, including comprehensive annotations per target, drug mechanism--action, approval dates, clinical trial phases various indications etc. data largely based drug-target-indication associations provided Open Targets Platform (Ochoa et al., Nucleic Acids Res., 2021). Associations retrieved Open Targets Platform integrated cancer-relevant indications/conditions (provided sigven/phenOncoX), allowing user retrieve drugs indicated main tumor types (e.g. Lung, Colon/Rectum etc.) Drug-target associations Open Targets Platform furthermore integrated appended drug information NCI Thesaurus, showing also non-targeted cancer drugs (chemotherapeutic agents etc.), various drug regimens. pharmOncoX provides anti-cancer drug classification existing entries Anatomical Therapeutic Chemical (ATC) Classification System, extended significantly manual curation, also establishing novel drug categories presently missing ATC classificiation tree (examples include AURK inhibitors, MET inhibitors, BET inhibitors, AKT inhibitors, PLK inhibitors, IAP inhibitors etc.) enabling filtering drugs according main mechanisms action. Currently (late Janurary 2024), pharmOncoX built upon following releases external databases: Open Targets Platform (2023.12) ChEMBL (v33) NCI Thesaurus (23.12d)","code":""},{"path":"https://sigven.github.io/pharmOncoX/index.html","id":"getting-started","dir":"","previous_headings":"","what":"Getting started","title":"Molecularly targeted cancer drugs and biomarkers","text":"Installation instructions Usage examples","code":""},{"path":"https://sigven.github.io/pharmOncoX/index.html","id":"contact","dir":"","previous_headings":"","what":"Contact","title":"Molecularly targeted cancer drugs and biomarkers","text":"sigven ifi.uio.","code":""},{"path":"https://sigven.github.io/pharmOncoX/index.html","id":"code-of-conduct","dir":"","previous_headings":"","what":"Code of Conduct","title":"Molecularly targeted cancer drugs and biomarkers","text":"Please note project released Contributor Code Conduct. participating project agree abide terms.","code":""},{"path":"https://sigven.github.io/pharmOncoX/reference/get_biomarkers.html","id":null,"dir":"Reference","previous_headings":"","what":"Get curated cancer biomarker datasets — get_biomarkers","title":"Get curated cancer biomarker datasets — get_biomarkers","text":"Downloads preprocessed datasets local cache directory returns curated set genomic biomarkers multiple sources (CIViC, CGI, MitelmanDB) dataset comes list object, three elements: metadata - data frame metadata regarding drug resources used data - list four elements ('civic','cgi','mitelmandb','custom_fusions') fpath - path cache file","code":""},{"path":"https://sigven.github.io/pharmOncoX/reference/get_biomarkers.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get curated cancer biomarker datasets — get_biomarkers","text":"","code":"get_biomarkers(cache_dir = NA, force_download = F)"},{"path":"https://sigven.github.io/pharmOncoX/reference/get_biomarkers.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get curated cancer biomarker datasets — get_biomarkers","text":"cache_dir Local directory data download force_download Logical indicating local cache force downloaded (.e. set TRUE re-download even data exists cache)","code":""},{"path":"https://sigven.github.io/pharmOncoX/reference/get_biomarkers.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get curated cancer biomarker datasets — get_biomarkers","text":"entry source-specific (e.g. 'civic') entry data list contains list three data frames: variant - list biomarker variants, extensively populated according variant aliases (identifer - column variant_id) clinical - cross-references variants recorded variant data frame clinical evidence items (identifier - column evidence_id) underlying literature evidence (identifier - column source_id) literature - lists literature source_id's listed clinical data frame","code":""},{"path":"https://sigven.github.io/pharmOncoX/reference/get_drug_records.html","id":null,"dir":"Reference","previous_headings":"","what":"Function that retrieves pharmOncoX data from Google Drive — get_drug_records","title":"Function that retrieves pharmOncoX data from Google Drive — get_drug_records","text":"Function retrieves pharmOncoX data Google Drive","code":""},{"path":"https://sigven.github.io/pharmOncoX/reference/get_drug_records.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Function that retrieves pharmOncoX data from Google Drive — get_drug_records","text":"","code":"get_drug_records(cache_dir = NA, force_download = F)"},{"path":"https://sigven.github.io/pharmOncoX/reference/get_drug_records.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Function that retrieves pharmOncoX data from Google Drive — get_drug_records","text":"cache_dir Local directory data download force_download Logical indicating local cache force downloaded (.e. set TRUE re-download even data exists cache)","code":""},{"path":"https://sigven.github.io/pharmOncoX/reference/get_drugs.html","id":null,"dir":"Reference","previous_headings":"","what":"Get antineoplastic drugs and drug regimens — get_drugs","title":"Get antineoplastic drugs and drug regimens — get_drugs","text":"Downloads preprocessed datasets local cache directory returns selected set drugs based various criteria set user. dataset comes list object, two elements: metadata - data frame metadata regarding drug resources used records - data frame drug records","code":""},{"path":"https://sigven.github.io/pharmOncoX/reference/get_drugs.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get antineoplastic drugs and drug regimens — get_drugs","text":"","code":"get_drugs( cache_dir = NA, force_download = FALSE, exclude_salt_forms = TRUE, exclude_adc = FALSE, treatment_category = c(\"targeted_therapy_classified\", \"targeted_therapy_unclassified\", \"chemo_therapy_classified\", \"hormone_therapy_classified\", \"immuno_suppressants_classified\", \"other\"), drug_is_approved = FALSE, drug_target = NULL, drug_action_type = NULL, drug_indication_main = NULL, drug_source_opentargets = FALSE, drug_cancer_indication = TRUE, drug_classified_cancer = TRUE, drug_has_blackbox_warning = FALSE, drug_approval_year = 1939, drug_minimum_phase_any_indication = 0, output_resolution = \"drug2target2indication\", drug_action_inhibition = F )"},{"path":"https://sigven.github.io/pharmOncoX/reference/get_drugs.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get antineoplastic drugs and drug regimens — get_drugs","text":"cache_dir local cache directory data retrieval force_download force download data remote repository even data exists cache exclude_salt_forms exclude salt forms drugs exclude_adc exclude antibody-drug conjugates (ADCs) treatment_category main treatment category, classified according ATC ('targeted_therapy_classified', 'targeted_therapy_unclassified','chemo_therapy_classified','hormone_therapy_classified', 'immuno_suppressants_classified','') drug_is_approved logical indicating resulting drug records contain approved drugs drug_target character vector drug targets (gene symbols) drug records included results drug_action_type character vector drug action types include drug record list - possible values \"INHIBITOR\",\"AGONIST\",\"MODULATOR\",\"ANTAGONIST\", \"BLOCKER\",\"ACTIVATOR\",\"BINDING AGENT\",\"OPENER\", \"STABILISER\",\"CROSS-LINKING AGENT\",DISRUPTING AGENT\",\"\" drug_indication_main character vector main tumor types drug(s) indicated. Possible values: \"Adrenal Gland\",\"Biliary Tract\", \"Bladder/Urinary Tract\",\"Bone\",\"Breast\",\"Cervix\",\"CNS/Brain\", \"Colon/Rectum\",\"Esophagus/Stomach\",\"Eye\",\"Head Neck\",\"Kidney\", \"Liver\",\"Lung\",\"Lymphoid\",\"Myeloid\",\"Ovary/Fallopian Tube\", \"Pancreas\",\"Penis\",\"Peripheral Nervous System\",\"Peritoneum\", \"Pleura\",\"Prostate\",\"Skin\",\"Soft Tissue\",\"Testis\",\"Thymus\", \"Thyroid\",\"Uterus\",\"Vulva/Vagina\" drug_source_opentargets logical indicating resulting drug records contain drug records Open Targets Platform/ChEMBL drug_cancer_indication logical indicating resulting drug records indicated cancer conditions (approved conditions, found clinical trials etc.) drug_classified_cancer logical indicating resulting drug records classified \"L\" class ATC ( \"ANTINEOPLASTIC IMMUNOMODULATING AGENTS\") drug_has_blackbox_warning logical indicating resulting drug records contain drugs black box warnings drug_approval_year include records drugs approved later date (year) drug_minimum_phase_any_indication include drug records clinical phase (indication) greater equal phase output_resolution dictate output record resolution ('drug','drug2target','drug2target2indication') drug_action_inhibition logical indicating return drug records inhibitory mechanism--action","code":""},{"path":"https://sigven.github.io/pharmOncoX/reference/get_drugs.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get antineoplastic drugs and drug regimens — get_drugs","text":"records data frame contains following columns (selected columns shown based value output_resolution) drug_id - drug identifier (pharmaOncoX) drug_name - primary drug name (upper case, NCI Thesaurus) drug_type - type drug molecule (Antibody, small molecule etc) molecule_chembl_id - ChEMBL compound identifier drug_action_type - main action elicited drug (antagonist, inhibitor, stabiliser etc) drug_alias - collection unambiguous drug aliases (separated '|') nci_concept_definition - detailed description drug mechanism--action (NCI Thesaurus) opentargets - logical - drug found Open Targets Platform resource is_salt - logical - drug record represents salt form (excluded default) is_adc - logical - drug record represents antibody-drug conjugate (ADC - excluded default) drug_blacbox_warning - logical indicating drug blackbox warning nci_t - NCI thesaurus identifier target_symbol - gene symbol drug target target_entrezgene - Entrez gene identifier drug target target_genename - gene name/description drug target target_ensembl_gene_id - Ensembl gene identifier drug target target_type - type drug target (single protein, protein family etc.) drug_max_phase_indication - maximum clinical phase drug (given indication) drug_approved_indication - logical indicating drug approved indication drug_frac_cancer_indications - fraction drug indications cancers drug_approved_noncancer - logical indicating drug approved non-cancer disease drug_n_indications - number indications given drug (approved indications, clinical trials etc) drug_year_first_approval - year drug first approved drug_max_ct_phase - maximum clinical phase drug (indication) disease_efo_id - EFO (Experimental Factor Ontology) identifier drug indication disease_efo_label - EFO (Experimental Factor Ontology) label drug indication primary_site - primary tumor site/type (obtained https://github.com/sigven/oncoPhenoMap) drug_clinical_id - drug clinical identifier (clinicaltrials.gov, DailyMed, FDA etc.) drug_clinical_source - underlying source drug entry (DailyMed, clinicaltrials.gov, FDA etc.) atc_code_level1 - drug identifier ATC (level 1) atc_level1 - drug label ATC (level 1) atc_code_level1 - drug identifier ATC (level 2) atc_level2 - drug label ATC (level 2) atc_code_level3 - drug identifier ATC (level 3) atc_level3 - drug label ATC (level 3) atc_treatment_category - treatment category (targeted/chemo/hormone, cancer/etc)","code":""},{"path":"https://sigven.github.io/pharmOncoX/reference/get_targeted_drugs.html","id":null,"dir":"Reference","previous_headings":"","what":"Utility function to get on-label/off-label drugs (not complete) — get_targeted_drugs","title":"Utility function to get on-label/off-label drugs (not complete) — get_targeted_drugs","text":"Utility function get -label/-label drugs (complete)","code":""},{"path":"https://sigven.github.io/pharmOncoX/reference/get_targeted_drugs.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Utility function to get on-label/off-label drugs (not complete) — get_targeted_drugs","text":"","code":"get_targeted_drugs(cache_dir = NA)"},{"path":"https://sigven.github.io/pharmOncoX/reference/get_targeted_drugs.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Utility function to get on-label/off-label drugs (not complete) — get_targeted_drugs","text":"cache_dir Local cache directory","code":""},{"path":"https://sigven.github.io/pharmOncoX/reference/tidyeval.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy eval helpers — tidyeval","title":"Tidy eval helpers — tidyeval","text":"https://cran.r-project.org/web/packages/dplyr/vignettes/programming.html","code":""},{"path":"https://sigven.github.io/pharmOncoX/news/index.html","id":"version-155-january-30th-2024","dir":"Changelog","previous_headings":"","what":"Version 1.5.5 (January 30th 2024)","title":"Version 1.5.5 (January 30th 2024)","text":"Refine possible values treatment_category argument get_drugs() function Fix anti-androgen classification Fixed bug alias type notation copy numbers expression biomarkers Filter noise rank output helper function get_targeted_drugs","code":""},{"path":"https://sigven.github.io/pharmOncoX/news/index.html","id":"version-150-january-25th-2024","dir":"Changelog","previous_headings":"","what":"Version 1.5.0 (January 25th 2024)","title":"Version 1.5.0 (January 25th 2024)","text":"Considerable improvement drug classifications (output column atc_level3), considering targeted agents chemotherapy argument drug_targeted_agent renamed treatment_category helper function get_on_off_label_drugs renamed get_targeted_drugs","code":""},{"path":"https://sigven.github.io/pharmOncoX/news/index.html","id":"version-1410-january-17th-2024","dir":"Changelog","previous_headings":"","what":"Version 1.4.10 (January 17th 2024)","title":"Version 1.4.10 (January 17th 2024)","text":"Updated NCI Thesaurus (23.12d) Updated CIViC data (20240114) Revised manual drug classification (building upon ATC)","code":""},{"path":"https://sigven.github.io/pharmOncoX/news/index.html","id":"version-148-december-12th-2023","dir":"Changelog","previous_headings":"","what":"Version 1.4.8 (December 12th 2023)","title":"Version 1.4.8 (December 12th 2023)","text":"Updated NCI Thesaurus - 23.11d Updated CIViC data (20231212)","code":""},{"path":"https://sigven.github.io/pharmOncoX/news/index.html","id":"version-148-november-30th-2023","dir":"Changelog","previous_headings":"","what":"Version 1.4.8 (November 30th 2023)","title":"Version 1.4.8 (November 30th 2023)","text":"Updated OTP (v2023.12) Updated Mitelman database (20231016)","code":""},{"path":"https://sigven.github.io/pharmOncoX/news/index.html","id":"version-147-november-3rd-2023","dir":"Changelog","previous_headings":"","what":"Version 1.4.7 (November 3rd 2023)","title":"Version 1.4.7 (November 3rd 2023)","text":"Fixed corrupt biomarker literature data frame","code":""},{"path":"https://sigven.github.io/pharmOncoX/news/index.html","id":"version-146-october-18th-2023","dir":"Changelog","previous_headings":"","what":"Version 1.4.6 (October 18th 2023)","title":"Version 1.4.6 (October 18th 2023)","text":"Fixed metadata Fixed -dated version descriptions (GH site) exclude compounds missing drug action type (platins etc.)","code":""},{"path":"https://sigven.github.io/pharmOncoX/news/index.html","id":"version-145-october-6th-2023","dir":"Changelog","previous_headings":"","what":"Version 1.4.5 (October 6th 2023)","title":"Version 1.4.5 (October 6th 2023)","text":"Updated NCI Thesaurus - 23.09d Updated CIViC data Added drug class (ATC) get_on_off_label_drugs()","code":""},{"path":"https://sigven.github.io/pharmOncoX/news/index.html","id":"version-144-september-1st-2023","dir":"Changelog","previous_headings":"","what":"Version 1.4.4 (September 1st 2023)","title":"Version 1.4.4 (September 1st 2023)","text":"Updated NCI Thesaurus - 23.08d Updated CIViC data Updated Mitelman database (20230803) get_biomarkers() now exported main function","code":""}] +[{"path":[]},{"path":"https://sigven.github.io/pharmOncoX/CODE_OF_CONDUCT.html","id":"our-pledge","dir":"","previous_headings":"","what":"Our Pledge","title":"Contributor Covenant Code of Conduct","text":"members, contributors, leaders pledge make participation community harassment-free experience everyone, regardless age, body size, visible invisible disability, ethnicity, sex characteristics, gender identity expression, level experience, education, socio-economic status, nationality, personal appearance, race, religion, sexual identity orientation. pledge act interact ways contribute open, welcoming, diverse, inclusive, healthy community.","code":""},{"path":"https://sigven.github.io/pharmOncoX/CODE_OF_CONDUCT.html","id":"our-standards","dir":"","previous_headings":"","what":"Our Standards","title":"Contributor Covenant Code of Conduct","text":"Examples behavior contributes positive environment community include: Demonstrating empathy kindness toward people respectful differing opinions, viewpoints, experiences Giving gracefully accepting constructive feedback Accepting responsibility apologizing affected mistakes, learning experience Focusing best just us individuals, overall community Examples unacceptable behavior include: use sexualized language imagery, sexual attention advances kind Trolling, insulting derogatory comments, personal political attacks Public private harassment Publishing others’ private information, physical email address, without explicit permission conduct reasonably considered inappropriate professional setting","code":""},{"path":"https://sigven.github.io/pharmOncoX/CODE_OF_CONDUCT.html","id":"enforcement-responsibilities","dir":"","previous_headings":"","what":"Enforcement Responsibilities","title":"Contributor Covenant Code of Conduct","text":"Community leaders responsible clarifying enforcing standards acceptable behavior take appropriate fair corrective action response behavior deem inappropriate, threatening, offensive, harmful. Community leaders right responsibility remove, edit, reject comments, commits, code, wiki edits, issues, contributions aligned Code Conduct, communicate reasons moderation decisions appropriate.","code":""},{"path":"https://sigven.github.io/pharmOncoX/CODE_OF_CONDUCT.html","id":"scope","dir":"","previous_headings":"","what":"Scope","title":"Contributor Covenant Code of Conduct","text":"Code Conduct applies within community spaces, also applies individual officially representing community public spaces. Examples representing community include using official e-mail address, posting via official social media account, acting appointed representative online offline event.","code":""},{"path":"https://sigven.github.io/pharmOncoX/CODE_OF_CONDUCT.html","id":"enforcement","dir":"","previous_headings":"","what":"Enforcement","title":"Contributor Covenant Code of Conduct","text":"Instances abusive, harassing, otherwise unacceptable behavior may reported community leaders responsible enforcement [INSERT CONTACT METHOD]. complaints reviewed investigated promptly fairly. community leaders obligated respect privacy security reporter incident.","code":""},{"path":"https://sigven.github.io/pharmOncoX/CODE_OF_CONDUCT.html","id":"enforcement-guidelines","dir":"","previous_headings":"","what":"Enforcement Guidelines","title":"Contributor Covenant Code of Conduct","text":"Community leaders follow Community Impact Guidelines determining consequences action deem violation Code Conduct:","code":""},{"path":"https://sigven.github.io/pharmOncoX/CODE_OF_CONDUCT.html","id":"id_1-correction","dir":"","previous_headings":"Enforcement Guidelines","what":"1. Correction","title":"Contributor Covenant Code of Conduct","text":"Community Impact: Use inappropriate language behavior deemed unprofessional unwelcome community. Consequence: private, written warning community leaders, providing clarity around nature violation explanation behavior inappropriate. public apology may requested.","code":""},{"path":"https://sigven.github.io/pharmOncoX/CODE_OF_CONDUCT.html","id":"id_2-warning","dir":"","previous_headings":"Enforcement Guidelines","what":"2. Warning","title":"Contributor Covenant Code of Conduct","text":"Community Impact: violation single incident series actions. Consequence: warning consequences continued behavior. interaction people involved, including unsolicited interaction enforcing Code Conduct, specified period time. includes avoiding interactions community spaces well external channels like social media. Violating terms may lead temporary permanent ban.","code":""},{"path":"https://sigven.github.io/pharmOncoX/CODE_OF_CONDUCT.html","id":"id_3-temporary-ban","dir":"","previous_headings":"Enforcement Guidelines","what":"3. Temporary Ban","title":"Contributor Covenant Code of Conduct","text":"Community Impact: serious violation community standards, including sustained inappropriate behavior. Consequence: temporary ban sort interaction public communication community specified period time. public private interaction people involved, including unsolicited interaction enforcing Code Conduct, allowed period. Violating terms may lead permanent ban.","code":""},{"path":"https://sigven.github.io/pharmOncoX/CODE_OF_CONDUCT.html","id":"id_4-permanent-ban","dir":"","previous_headings":"Enforcement Guidelines","what":"4. Permanent Ban","title":"Contributor Covenant Code of Conduct","text":"Community Impact: Demonstrating pattern violation community standards, including sustained inappropriate behavior, harassment individual, aggression toward disparagement classes individuals. Consequence: permanent ban sort public interaction within community.","code":""},{"path":"https://sigven.github.io/pharmOncoX/CODE_OF_CONDUCT.html","id":"attribution","dir":"","previous_headings":"","what":"Attribution","title":"Contributor Covenant Code of Conduct","text":"Code Conduct adapted Contributor Covenant, version 2.0, available https://www.contributor-covenant.org/version/2/0/ code_of_conduct.html. Community Impact Guidelines inspired Mozilla’s code conduct enforcement ladder. answers common questions code conduct, see FAQ https://www.contributor-covenant.org/faq. Translations available https:// www.contributor-covenant.org/translations.","code":""},{"path":"https://sigven.github.io/pharmOncoX/articles/pharmOncoX.html","id":"installation","dir":"Articles","previous_headings":"","what":"Installation","title":"Getting started","text":"","code":"if (!(\"remotes\" %in% installed.packages())) { install.packages(\"remotes\") } remotes::install_github('sigven/pharmOncoX') #> Using github PAT from envvar GITHUB_PAT #> Downloading GitHub repo sigven/pharmOncoX@HEAD #> #> ── R CMD build ───────────────────────────────────────────────────────────────── #> * checking for file ‘/tmp/RtmpsbEbNc/remotes18c6def612b/sigven-pharmOncoX-808bd39/DESCRIPTION’ ... OK #> * preparing ‘pharmOncoX’: #> * checking DESCRIPTION meta-information ... OK #> * checking for LF line-endings in source and make files and shell scripts #> * checking for empty or unneeded directories #> Omitted ‘LazyData’ from DESCRIPTION #> * building ‘pharmOncoX_1.5.6.tar.gz’ #> Installing package into '/home/runner/work/_temp/Library' #> (as 'lib' is unspecified) library(pharmOncoX) cache_dir <- tempdir()"},{"path":[]},{"path":"https://sigven.github.io/pharmOncoX/articles/pharmOncoX.html","id":"targeted-agents","dir":"Articles","previous_headings":"Cancer drug classifications","what":"Targeted agents","title":"Getting started","text":"Plotted key statistics respect drug classification numbers targeted chemotherapy agents found pharmOncoX. Existing drug classifications retrieved ATC, extended manual addition/curation, also establishment multiple novel levels ATC tree, particularly targeted therapies. Note drugs indicated cancer conditions (harvested Open Targets platform) considered numbers plotted .","code":"p_targeted_classifications"},{"path":"https://sigven.github.io/pharmOncoX/articles/pharmOncoX.html","id":"chemotherapy-agents","dir":"Articles","previous_headings":"Cancer drug classifications","what":"Chemotherapy agents","title":"Getting started","text":"","code":"p_chemo_classifications"},{"path":[]},{"path":"https://sigven.github.io/pharmOncoX/articles/pharmOncoX.html","id":"get-braf-targeted-drugs-list-records-per-indication","dir":"Articles","previous_headings":"Retrieval of drugs - examples","what":"Get BRAF-targeted drugs, list records per indication","title":"Getting started","text":"","code":"drugs <- get_drugs( cache_dir = cache_dir, treatment_category = c(\"targeted_therapy_classified\", \"targeted_therapy_unclassified\"), drug_target = c('BRAF')) #> INFO [2024-01-31 09:52:38] Reading from cache_dir = '/tmp/RtmpsbEbNc', argument force_download = F #> INFO [2024-01-31 09:52:38] Object 'drug_map_name' sucessfully loaded #> INFO [2024-01-31 09:52:38] Retrieved n = 31302 records #> INFO [2024-01-31 09:52:38] Reading from cache_dir = '/tmp/RtmpsbEbNc', argument force_download = F #> INFO [2024-01-31 09:52:38] Object 'drug_map_alias' sucessfully loaded #> INFO [2024-01-31 09:52:38] Retrieved n = 677250 records #> INFO [2024-01-31 09:52:38] Reading from cache_dir = '/tmp/RtmpsbEbNc', argument force_download = F #> INFO [2024-01-31 09:52:38] Object 'drug_map_basic' sucessfully loaded #> INFO [2024-01-31 09:52:38] Retrieved n = 31337 records #> INFO [2024-01-31 09:52:38] Reading from cache_dir = '/tmp/RtmpsbEbNc', argument force_download = F #> INFO [2024-01-31 09:52:38] Object 'drug_map_target' sucessfully loaded #> INFO [2024-01-31 09:52:38] Retrieved n = 39211 records #> INFO [2024-01-31 09:52:39] Reading from cache_dir = '/tmp/RtmpsbEbNc', argument force_download = F #> INFO [2024-01-31 09:52:39] Object 'drug_map_indication' sucessfully loaded #> INFO [2024-01-31 09:52:39] Retrieved n = 64079 records #> INFO [2024-01-31 09:52:41] Record set satisfying user-defined criteria: n = 296 #> INFO [2024-01-31 09:52:41] Collapsing record set - providing output on a 'per_drug_target_indication' resolution #> INFO [2024-01-31 09:52:41] Final record set: n = 254 records ## Number of drug records nrow(drugs$records) #> [1] 254 ## Column names of drug records colnames(drugs$records) #> [1] \"drug_id\" \"drug_name\" #> [3] \"drug_type\" \"molecule_chembl_id\" #> [5] \"drug_action_type\" \"drug_alias\" #> [7] \"nci_concept_definition\" \"opentargets\" #> [9] \"drug_cancer_relevance\" \"inhibition_moa\" #> [11] \"is_salt\" \"is_adc\" #> [13] \"drug_blackbox_warning\" \"nci_t\" #> [15] \"target_symbol\" \"target_entrezgene\" #> [17] \"target_genename\" \"target_ensembl_gene_id\" #> [19] \"target_type\" \"drug_max_phase_indication\" #> [21] \"drug_approved_indication\" \"drug_frac_cancer_indications\" #> [23] \"drug_approved_noncancer\" \"drug_n_indications\" #> [25] \"drug_year_first_approval\" \"drug_max_ct_phase\" #> [27] \"disease_efo_id\" \"disease_efo_label\" #> [29] \"primary_site\" \"drug_clinical_id\" #> [31] \"drug_clinical_source\" \"atc_code_level1\" #> [33] \"atc_level1\" \"atc_code_level2\" #> [35] \"atc_level2\" \"atc_code_level3\" #> [37] \"atc_level3\" \"atc_treatment_category\""},{"path":"https://sigven.github.io/pharmOncoX/articles/pharmOncoX.html","id":"get-ras-targeted-drugs-list-per-drug-target","dir":"Articles","previous_headings":"Retrieval of drugs - examples","what":"Get RAS-targeted drugs, list per drug target","title":"Getting started","text":"","code":"drugs <- get_drugs( cache_dir = cache_dir, treatment_category = c(\"targeted_therapy_classified\"), drug_action_inhibition = T, output_resolution = \"drug2target\")$records |> dplyr::filter(atc_level3 == \"RAS inhibitors\") drugs <- drugs |> dplyr::select( -c(\"drug_alias\", \"disease_main_group\", \"drug_clinical_id\")) |> dplyr::mutate( disease_indication = stringr::str_replace_all( disease_indication, \"\\\\|\",\", \") ) dt_drugtable_ras_inhibitors <- DT::datatable( drugs, escape = FALSE, extensions = c(\"Buttons\", \"Responsive\"), width = \"100%\", options = list( buttons = c(\"csv\", \"excel\"), dom = \"Bfrtip\") )"},{"path":"https://sigven.github.io/pharmOncoX/articles/pharmOncoX.html","id":"get-mek-inhibitors-list-per-drug-only","dir":"Articles","previous_headings":"Retrieval of drugs - examples","what":"Get MEK inhibitors, list per drug only","title":"Getting started","text":"","code":"drugs <- get_drugs( cache_dir = cache_dir, treatment_category = c(\"targeted_therapy_classified\"), drug_action_inhibition = T, drug_source_opentargets = T, output_resolution = \"drug\" )$records |> dplyr::filter(atc_level3 == \"MEK inhibitors\") drugs <- drugs |> dplyr::select( -c(\"drug_alias\", \"disease_main_group\", \"drug_clinical_id\")) |> dplyr::mutate( disease_indication = stringr::str_replace_all( disease_indication, \"\\\\|\",\", \") ) dt_drugtable_mek_inhibitors <- DT::datatable( drugs, escape = FALSE, extensions = c(\"Buttons\", \"Responsive\"), width = \"100%\", options = list( buttons = c(\"csv\", \"excel\"), dom = \"Bfrtip\") )"},{"path":"https://sigven.github.io/pharmOncoX/articles/pharmOncoX.html","id":"get-immune-checkpoint-inhibitors-list-per-drug-target","dir":"Articles","previous_headings":"Retrieval of drugs - examples","what":"Get immune checkpoint inhibitors, list per drug target","title":"Getting started","text":"","code":"drugs <- get_drugs( cache_dir = cache_dir, treatment_category = c(\"targeted_therapy_classified\"), drug_source_opentargets = F, drug_classified_cancer = T, output_resolution = \"drug2target\") drugs$records <- drugs$records |> dplyr::filter( (!is.na(atc_level3) & (atc_level3 == \"PD-1/PDL-1 inhibitors\" | atc_level3 == \"Other immune checkpoint inhibitors\") )) |> dplyr::select( -c(\"drug_alias\", \"disease_main_group\", \"drug_clinical_id\")) |> dplyr::mutate( disease_indication = stringr::str_replace_all( disease_indication, \"\\\\|\",\", \") ) |> dplyr::select( drug_id, drug_name, drug_type, target_symbol, target_genename, dplyr::everything() ) dt_drugtable_ici <- DT::datatable( drugs$records, escape = FALSE, extensions = c(\"Buttons\", \"Responsive\"), width = \"100%\", options = list( buttons = c(\"csv\", \"excel\"), dom = \"Bfrtip\") )"},{"path":"https://sigven.github.io/pharmOncoX/articles/pharmOncoX.html","id":"get-immune-checkpoint-inhibitors-indicated-for-lung-cancer-conditions-list-per-drug-target-entry","dir":"Articles","previous_headings":"Retrieval of drugs - examples","what":"Get immune checkpoint inhibitors indicated for lung cancer conditions, list per drug-target entry","title":"Getting started","text":"","code":"drugs <- get_drugs( cache_dir = cache_dir, output_resolution = \"drug2target\", treatment_category = c(\"targeted_therapy_classified\"), drug_source_opentargets = T, drug_indication_main = \"Lung\") drugs$records <- drugs$records |> dplyr::filter( (!is.na(atc_level3) & (atc_level3 == \"PD-1/PDL-1 inhibitors\" | atc_level3 == \"Other immune checkpoint inhibitors\") )) |> dplyr::select( -c(\"drug_alias\", \"disease_main_group\", \"drug_clinical_id\")) |> dplyr::mutate( disease_indication = stringr::str_replace_all( disease_indication, \"\\\\|\",\", \") ) |> dplyr::select( drug_id, drug_name, drug_type, target_symbol, target_genename, dplyr::everything() ) dt_drugtable_ici_lung <- DT::datatable( drugs$records, escape = FALSE, extensions = c(\"Buttons\", \"Responsive\"), width = \"100%\", options = list( buttons = c(\"csv\", \"excel\"), dom = \"Bfrtip\") )"},{"path":"https://sigven.github.io/pharmOncoX/articles/pharmOncoX.html","id":"get-antimetabolite-drugs","dir":"Articles","previous_headings":"Retrieval of drugs - examples","what":"Get antimetabolite drugs","title":"Getting started","text":"","code":"drugs <- get_drugs( cache_dir = cache_dir, treatment_category = c(\"chemo_therapy_classified\"), output_resolution = \"drug\") #> INFO [2024-01-31 09:53:05] Reading from cache_dir = '/tmp/RtmpsbEbNc', argument force_download = F #> INFO [2024-01-31 09:53:05] Object 'drug_map_name' sucessfully loaded #> INFO [2024-01-31 09:53:05] Retrieved n = 31302 records #> INFO [2024-01-31 09:53:05] Reading from cache_dir = '/tmp/RtmpsbEbNc', argument force_download = F #> INFO [2024-01-31 09:53:05] Object 'drug_map_alias' sucessfully loaded #> INFO [2024-01-31 09:53:05] Retrieved n = 677250 records #> INFO [2024-01-31 09:53:05] Reading from cache_dir = '/tmp/RtmpsbEbNc', argument force_download = F #> INFO [2024-01-31 09:53:05] Object 'drug_map_basic' sucessfully loaded #> INFO [2024-01-31 09:53:05] Retrieved n = 31337 records #> INFO [2024-01-31 09:53:05] Reading from cache_dir = '/tmp/RtmpsbEbNc', argument force_download = F #> INFO [2024-01-31 09:53:05] Object 'drug_map_target' sucessfully loaded #> INFO [2024-01-31 09:53:05] Retrieved n = 39211 records #> INFO [2024-01-31 09:53:05] Reading from cache_dir = '/tmp/RtmpsbEbNc', argument force_download = F #> INFO [2024-01-31 09:53:05] Object 'drug_map_indication' sucessfully loaded #> INFO [2024-01-31 09:53:05] Retrieved n = 64079 records #> INFO [2024-01-31 09:53:08] Record set satisfying user-defined criteria: n = 16409 #> INFO [2024-01-31 09:53:08] Collapsing record set - providing output on a 'per_drug' resolution #> INFO [2024-01-31 09:53:08] Final record set: n = 146 records drugs$records <- drugs$records |> dplyr::filter( !is.na(atc_level2) & stringr::str_detect( atc_level2, \"ANTIMETABOLITES\" ) ) |> dplyr::select( -c(\"drug_alias\", \"disease_main_group\", \"drug_clinical_id\")) |> dplyr::mutate( disease_indication = stringr::str_replace_all( disease_indication, \"\\\\|\",\", \") ) dt_drugtable_metabolites <- DT::datatable( drugs$records, escape = FALSE, extensions = c(\"Buttons\", \"Responsive\"), width = \"100%\", options = list( buttons = c(\"csv\", \"excel\"), dom = \"Bfrtip\") )"},{"path":"https://sigven.github.io/pharmOncoX/articles/pharmOncoX.html","id":"get-taxanes","dir":"Articles","previous_headings":"Retrieval of drugs - examples","what":"Get taxanes","title":"Getting started","text":"","code":"drugs <- get_drugs( cache_dir = cache_dir, treatment_category = \"chemo_therapy_classified\", output_resolution = \"drug\") #> INFO [2024-01-31 09:53:09] Reading from cache_dir = '/tmp/RtmpsbEbNc', argument force_download = F #> INFO [2024-01-31 09:53:09] Object 'drug_map_name' sucessfully loaded #> INFO [2024-01-31 09:53:09] Retrieved n = 31302 records #> INFO [2024-01-31 09:53:09] Reading from cache_dir = '/tmp/RtmpsbEbNc', argument force_download = F #> INFO [2024-01-31 09:53:09] Object 'drug_map_alias' sucessfully loaded #> INFO [2024-01-31 09:53:09] Retrieved n = 677250 records #> INFO [2024-01-31 09:53:09] Reading from cache_dir = '/tmp/RtmpsbEbNc', argument force_download = F #> INFO [2024-01-31 09:53:09] Object 'drug_map_basic' sucessfully loaded #> INFO [2024-01-31 09:53:09] Retrieved n = 31337 records #> INFO [2024-01-31 09:53:09] Reading from cache_dir = '/tmp/RtmpsbEbNc', argument force_download = F #> INFO [2024-01-31 09:53:09] Object 'drug_map_target' sucessfully loaded #> INFO [2024-01-31 09:53:09] Retrieved n = 39211 records #> INFO [2024-01-31 09:53:09] Reading from cache_dir = '/tmp/RtmpsbEbNc', argument force_download = F #> INFO [2024-01-31 09:53:09] Object 'drug_map_indication' sucessfully loaded #> INFO [2024-01-31 09:53:09] Retrieved n = 64079 records #> INFO [2024-01-31 09:53:12] Record set satisfying user-defined criteria: n = 16409 #> INFO [2024-01-31 09:53:12] Collapsing record set - providing output on a 'per_drug' resolution #> INFO [2024-01-31 09:53:12] Final record set: n = 146 records drugs$records <- drugs$records |> dplyr::filter( stringr::str_detect( atc_level3, \"Taxanes\" ) ) |> dplyr::select( -c(\"drug_alias\", \"disease_main_group\", \"drug_clinical_id\")) |> dplyr::mutate( disease_indication = stringr::str_replace_all( disease_indication, \"\\\\|\",\", \") ) dt_drugtable_taxanes <- DT::datatable( drugs$records, escape = FALSE, extensions = c(\"Buttons\", \"Responsive\"), width = \"100%\", options = list( buttons = c(\"csv\", \"excel\"), dom = \"Bfrtip\") )"},{"path":"https://sigven.github.io/pharmOncoX/articles/pharmOncoX.html","id":"get-platinum-compounds","dir":"Articles","previous_headings":"Retrieval of drugs - examples","what":"Get platinum compounds","title":"Getting started","text":"","code":"drugs <- get_drugs( cache_dir = cache_dir, treatment_category = \"chemo_therapy_classified\", output_resolution = \"drug\") #> INFO [2024-01-31 09:53:13] Reading from cache_dir = '/tmp/RtmpsbEbNc', argument force_download = F #> INFO [2024-01-31 09:53:13] Object 'drug_map_name' sucessfully loaded #> INFO [2024-01-31 09:53:13] Retrieved n = 31302 records #> INFO [2024-01-31 09:53:13] Reading from cache_dir = '/tmp/RtmpsbEbNc', argument force_download = F #> INFO [2024-01-31 09:53:13] Object 'drug_map_alias' sucessfully loaded #> INFO [2024-01-31 09:53:13] Retrieved n = 677250 records #> INFO [2024-01-31 09:53:13] Reading from cache_dir = '/tmp/RtmpsbEbNc', argument force_download = F #> INFO [2024-01-31 09:53:13] Object 'drug_map_basic' sucessfully loaded #> INFO [2024-01-31 09:53:13] Retrieved n = 31337 records #> INFO [2024-01-31 09:53:13] Reading from cache_dir = '/tmp/RtmpsbEbNc', argument force_download = F #> INFO [2024-01-31 09:53:13] Object 'drug_map_target' sucessfully loaded #> INFO [2024-01-31 09:53:13] Retrieved n = 39211 records #> INFO [2024-01-31 09:53:13] Reading from cache_dir = '/tmp/RtmpsbEbNc', argument force_download = F #> INFO [2024-01-31 09:53:13] Object 'drug_map_indication' sucessfully loaded #> INFO [2024-01-31 09:53:13] Retrieved n = 64079 records #> INFO [2024-01-31 09:53:16] Record set satisfying user-defined criteria: n = 16409 #> INFO [2024-01-31 09:53:16] Collapsing record set - providing output on a 'per_drug' resolution #> INFO [2024-01-31 09:53:16] Final record set: n = 146 records drugs$records <- drugs$records |> dplyr::filter( stringr::str_detect( atc_level3, \"Platinum compounds\" ) ) |> dplyr::select( -c(\"drug_alias\", \"disease_main_group\", \"drug_clinical_id\")) |> dplyr::mutate( disease_indication = stringr::str_replace_all( disease_indication, \"\\\\|\",\", \") ) dt_drugtable_platins <- DT::datatable( drugs$records, escape = FALSE, extensions = c(\"Buttons\", \"Responsive\"), width = \"100%\", options = list( buttons = c(\"csv\", \"excel\"), dom = \"Bfrtip\") )"},{"path":[]},{"path":"https://sigven.github.io/pharmOncoX/articles/pharmOncoX.html","id":"reported-associations-between-brca12-alterations-and-drug-sensitivity","dir":"Articles","previous_headings":"Retrieval of biomarkers","what":"Reported associations between BRCA1/2 alterations and drug sensitivity","title":"Getting started","text":"Get evidence CIViC CGI cancer drug sensitivity BRCA1/2 alterations (somatically (tumor) inherited/germline)","code":"biomarkers <- get_biomarkers( cache_dir = cache_dir) #> INFO [2024-01-31 09:53:17] Downloading remote dataset from Google Drive to cache_dir #> INFO [2024-01-31 09:53:20] Reading from cache_dir = ' (/tmp/RtmpsbEbNc'), argument force_download = F #> INFO [2024-01-31 09:53:20] Object 'biomarkers' sucessfully loaded #> INFO [2024-01-31 09:53:20] md5 checksum is valid: 98fcfe1b54c2b393112c0be81e58fc9e brca1_biomarkers <- list() for(source in c('civic','cgi')){ brca1_biomarkers[[source]] <- biomarkers$data[[source]]$variant |> dplyr::filter( !is.na(symbol) & (symbol == \"BRCA1\" | symbol == \"BRCA2\")) |> dplyr::group_by(variant_id, symbol, variant_consequence) |> dplyr::summarise( variant_alias = paste(variant_alias, collapse=\", \"), .groups = \"drop\") |> dplyr::inner_join( biomarkers$data[[source]]$clinical, by = \"variant_id\") |> dplyr::select( variant_id, symbol, variant_consequence, variant_alias, biomarker_source, biomarker_source_datestamp, molecular_profile_name, evidence_id, variant_origin, primary_site, evidence_id, source_id, evidence_url, therapeutic_context, evidence_description, evidence_type, evidence_level, clinical_significance) |> dplyr::distinct() |> dplyr::rename(literature_id = source_id) |> dplyr::filter(evidence_type == \"Predictive\") |> dplyr::select( symbol, primary_site, therapeutic_context, molecular_profile_name, evidence_level, dplyr::everything() ) } brca1_biomarkers_all <- dplyr::bind_rows(brca1_biomarkers[['civic']], brca1_biomarkers[['cgi']]) |> dplyr::arrange(evidence_level) dt_brca1_biomarkers <- DT::datatable( brca1_biomarkers_all, escape = FALSE, extensions = c(\"Buttons\", \"Responsive\"), width = \"100%\", options = list( buttons = c(\"csv\", \"excel\"), dom = \"Bfrtip\") )"},{"path":"https://sigven.github.io/pharmOncoX/articles/pharmOncoX.html","id":"session-info","dir":"Articles","previous_headings":"","what":"Session Info","title":"Getting started","text":"","code":"# set eval = FALSE if you don't want this info (useful for reproducibility) # to appear sessionInfo() #> R version 4.3.2 (2023-10-31) #> Platform: x86_64-pc-linux-gnu (64-bit) #> Running under: Ubuntu 22.04.3 LTS #> #> Matrix products: default #> BLAS: /usr/lib/x86_64-linux-gnu/openblas-pthread/libblas.so.3 #> LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.20.so; LAPACK version 3.10.0 #> #> locale: #> [1] LC_CTYPE=C.UTF-8 LC_NUMERIC=C LC_TIME=C.UTF-8 #> [4] LC_COLLATE=C.UTF-8 LC_MONETARY=C.UTF-8 LC_MESSAGES=C.UTF-8 #> [7] LC_PAPER=C.UTF-8 LC_NAME=C LC_ADDRESS=C #> [10] LC_TELEPHONE=C LC_MEASUREMENT=C.UTF-8 LC_IDENTIFICATION=C #> #> time zone: UTC #> tzcode source: system (glibc) #> #> attached base packages: #> [1] stats graphics grDevices utils datasets methods base #> #> other attached packages: #> [1] pharmOncoX_1.5.6 #> #> loaded via a namespace (and not attached): #> [1] sass_0.4.8 utf8_1.2.4 generics_0.1.3 stringi_1.8.3 #> [5] digest_0.6.34 magrittr_2.0.3 grid_4.3.2 evaluate_0.23 #> [9] fastmap_1.1.1 jsonlite_1.8.8 processx_3.8.3 pkgbuild_1.4.3 #> [13] googledrive_2.1.1 ps_1.7.6 httr_1.4.7 purrr_1.0.2 #> [17] fansi_1.0.6 crosstalk_1.2.1 scales_1.3.0 textshaping_0.3.7 #> [21] jquerylib_0.1.4 cli_3.6.2 rlang_1.1.3 crayon_1.5.2 #> [25] ellipsis_0.3.2 munsell_0.5.0 remotes_2.4.2.1 withr_3.0.0 #> [29] cachem_1.0.8 yaml_2.3.8 tools_4.3.2 gargle_1.5.2 #> [33] memoise_2.0.1 dplyr_1.1.4 colorspace_2.1-0 ggplot2_3.4.4 #> [37] DT_0.31 curl_5.2.0 assertthat_0.2.1 vctrs_0.6.5 #> [41] R6_2.5.1 lifecycle_1.0.4 stringr_1.5.1 htmlwidgets_1.6.4 #> [45] fs_1.6.3 ragg_1.2.7 pkgconfig_2.0.3 desc_1.4.3 #> [49] callr_3.7.3 gtable_0.3.4 pkgdown_2.0.7 bslib_0.6.1 #> [53] pillar_1.9.0 glue_1.7.0 lgr_0.4.4 systemfonts_1.0.5 #> [57] highr_0.10 xfun_0.41 tibble_3.2.1 tidyselect_1.2.0 #> [61] knitr_1.45 farver_2.1.1 htmltools_0.5.7 rmarkdown_2.25 #> [65] compiler_4.3.2"},{"path":[]},{"path":"https://sigven.github.io/pharmOncoX/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Sigve Nakken. Author, maintainer.","code":""},{"path":"https://sigven.github.io/pharmOncoX/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Nakken S. (2023) pharmOncoX: Targeted non-targeted anti-cancer drugs drug regimens. R package version 1.5.6. (https://github.com/sigven/pharmOncoX)","code":"@Manual{, title = {pharmOncoX: Targeted and non-targeted anti-cancer drugs and drug regimens}, author = {Sigve Nakken}, year = {2023}, note = {R package version 1.5.6}, url = {https://github.com/sigven/pharmOncoX}, }"},{"path":"https://sigven.github.io/pharmOncoX/index.html","id":"pharmoncox-","dir":"","previous_headings":"","what":"Molecularly targeted cancer drugs and biomarkers","title":"Molecularly targeted cancer drugs and biomarkers","text":"pharmOncoX provides access targeted non-targeted cancer drugs, including comprehensive annotations per target, drug mechanism--action, approval dates, clinical trial phases various indications etc. data largely based drug-target-indication associations provided Open Targets Platform (Ochoa et al., Nucleic Acids Res., 2021). Associations retrieved Open Targets Platform integrated cancer-relevant indications/conditions (provided sigven/phenOncoX), allowing user retrieve drugs indicated main tumor types (e.g. Lung, Colon/Rectum etc.) Drug-target associations Open Targets Platform furthermore integrated appended drug information NCI Thesaurus, showing also non-targeted cancer drugs (chemotherapeutic agents etc.), various drug regimens. pharmOncoX provides anti-cancer drug classification existing entries Anatomical Therapeutic Chemical (ATC) Classification System, extended significantly manual curation, also establishing novel drug categories presently missing ATC classificiation tree (examples include AURK inhibitors, MET inhibitors, BET inhibitors, AKT inhibitors, PLK inhibitors, IAP inhibitors etc.) enabling filtering drugs according main mechanisms action. Currently (late Janurary 2024), pharmOncoX built upon following releases external databases: Open Targets Platform (2023.12) ChEMBL (v33) NCI Thesaurus (23.12d)","code":""},{"path":"https://sigven.github.io/pharmOncoX/index.html","id":"getting-started","dir":"","previous_headings":"","what":"Getting started","title":"Molecularly targeted cancer drugs and biomarkers","text":"Installation instructions Usage examples","code":""},{"path":"https://sigven.github.io/pharmOncoX/index.html","id":"contact","dir":"","previous_headings":"","what":"Contact","title":"Molecularly targeted cancer drugs and biomarkers","text":"sigven ifi.uio.","code":""},{"path":"https://sigven.github.io/pharmOncoX/index.html","id":"code-of-conduct","dir":"","previous_headings":"","what":"Code of Conduct","title":"Molecularly targeted cancer drugs and biomarkers","text":"Please note project released Contributor Code Conduct. participating project agree abide terms.","code":""},{"path":"https://sigven.github.io/pharmOncoX/reference/get_biomarkers.html","id":null,"dir":"Reference","previous_headings":"","what":"Get curated cancer biomarker datasets — get_biomarkers","title":"Get curated cancer biomarker datasets — get_biomarkers","text":"Downloads preprocessed datasets local cache directory returns curated set genomic biomarkers multiple sources (CIViC, CGI, MitelmanDB) dataset comes list object, three elements: metadata - data frame metadata regarding drug resources used data - list four elements ('civic','cgi','mitelmandb','custom_fusions') fpath - path cache file","code":""},{"path":"https://sigven.github.io/pharmOncoX/reference/get_biomarkers.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get curated cancer biomarker datasets — get_biomarkers","text":"","code":"get_biomarkers(cache_dir = NA, force_download = F)"},{"path":"https://sigven.github.io/pharmOncoX/reference/get_biomarkers.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get curated cancer biomarker datasets — get_biomarkers","text":"cache_dir Local directory data download force_download Logical indicating local cache force downloaded (.e. set TRUE re-download even data exists cache)","code":""},{"path":"https://sigven.github.io/pharmOncoX/reference/get_biomarkers.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get curated cancer biomarker datasets — get_biomarkers","text":"entry source-specific (e.g. 'civic') entry data list contains list three data frames: variant - list biomarker variants, extensively populated according variant aliases (identifer - column variant_id) clinical - cross-references variants recorded variant data frame clinical evidence items (identifier - column evidence_id) underlying literature evidence (identifier - column source_id) literature - lists literature source_id's listed clinical data frame","code":""},{"path":"https://sigven.github.io/pharmOncoX/reference/get_drug_records.html","id":null,"dir":"Reference","previous_headings":"","what":"Function that retrieves pharmOncoX data from Google Drive — get_drug_records","title":"Function that retrieves pharmOncoX data from Google Drive — get_drug_records","text":"Function retrieves pharmOncoX data Google Drive","code":""},{"path":"https://sigven.github.io/pharmOncoX/reference/get_drug_records.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Function that retrieves pharmOncoX data from Google Drive — get_drug_records","text":"","code":"get_drug_records(cache_dir = NA, force_download = F)"},{"path":"https://sigven.github.io/pharmOncoX/reference/get_drug_records.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Function that retrieves pharmOncoX data from Google Drive — get_drug_records","text":"cache_dir Local directory data download force_download Logical indicating local cache force downloaded (.e. set TRUE re-download even data exists cache)","code":""},{"path":"https://sigven.github.io/pharmOncoX/reference/get_drugs.html","id":null,"dir":"Reference","previous_headings":"","what":"Get antineoplastic drugs and drug regimens — get_drugs","title":"Get antineoplastic drugs and drug regimens — get_drugs","text":"Downloads preprocessed datasets local cache directory returns selected set drugs based various criteria set user. dataset comes list object, two elements: metadata - data frame metadata regarding drug resources used records - data frame drug records","code":""},{"path":"https://sigven.github.io/pharmOncoX/reference/get_drugs.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get antineoplastic drugs and drug regimens — get_drugs","text":"","code":"get_drugs( cache_dir = NA, force_download = FALSE, exclude_salt_forms = TRUE, exclude_adc = FALSE, treatment_category = c(\"targeted_therapy_classified\", \"targeted_therapy_unclassified\", \"chemo_therapy_classified\", \"hormone_therapy_classified\", \"immuno_suppressants_classified\", \"other\"), drug_is_approved = FALSE, drug_target = NULL, drug_action_type = NULL, drug_indication_main = NULL, drug_source_opentargets = FALSE, drug_cancer_indication = TRUE, drug_classified_cancer = TRUE, drug_has_blackbox_warning = FALSE, drug_approval_year = 1939, drug_minimum_phase_any_indication = 0, output_resolution = \"drug2target2indication\", drug_action_inhibition = F )"},{"path":"https://sigven.github.io/pharmOncoX/reference/get_drugs.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get antineoplastic drugs and drug regimens — get_drugs","text":"cache_dir local cache directory data retrieval force_download force download data remote repository even data exists cache exclude_salt_forms exclude salt forms drugs exclude_adc exclude antibody-drug conjugates (ADCs) treatment_category main treatment category, classified according ATC ('targeted_therapy_classified', 'targeted_therapy_unclassified','chemo_therapy_classified','hormone_therapy_classified', 'immuno_suppressants_classified','') drug_is_approved logical indicating resulting drug records contain approved drugs drug_target character vector drug targets (gene symbols) drug records included results drug_action_type character vector drug action types include drug record list - possible values \"INHIBITOR\",\"AGONIST\",\"MODULATOR\",\"ANTAGONIST\", \"BLOCKER\",\"ACTIVATOR\",\"BINDING AGENT\",\"OPENER\", \"STABILISER\",\"CROSS-LINKING AGENT\",DISRUPTING AGENT\",\"\" drug_indication_main character vector main tumor types drug(s) indicated. Possible values: \"Adrenal Gland\",\"Biliary Tract\", \"Bladder/Urinary Tract\",\"Bone\",\"Breast\",\"Cervix\",\"CNS/Brain\", \"Colon/Rectum\",\"Esophagus/Stomach\",\"Eye\",\"Head Neck\",\"Kidney\", \"Liver\",\"Lung\",\"Lymphoid\",\"Myeloid\",\"Ovary/Fallopian Tube\", \"Pancreas\",\"Penis\",\"Peripheral Nervous System\",\"Peritoneum\", \"Pleura\",\"Prostate\",\"Skin\",\"Soft Tissue\",\"Testis\",\"Thymus\", \"Thyroid\",\"Uterus\",\"Vulva/Vagina\" drug_source_opentargets logical indicating resulting drug records contain drug records Open Targets Platform/ChEMBL drug_cancer_indication logical indicating resulting drug records indicated cancer conditions (approved conditions, found clinical trials etc.) drug_classified_cancer logical indicating resulting drug records classified \"L\" class ATC ( \"ANTINEOPLASTIC IMMUNOMODULATING AGENTS\") drug_has_blackbox_warning logical indicating resulting drug records contain drugs black box warnings drug_approval_year include records drugs approved later date (year) drug_minimum_phase_any_indication include drug records clinical phase (indication) greater equal phase output_resolution dictate output record resolution ('drug','drug2target','drug2target2indication') drug_action_inhibition logical indicating return drug records inhibitory mechanism--action","code":""},{"path":"https://sigven.github.io/pharmOncoX/reference/get_drugs.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get antineoplastic drugs and drug regimens — get_drugs","text":"records data frame contains following columns (selected columns shown based value output_resolution) drug_id - drug identifier (pharmaOncoX) drug_name - primary drug name (upper case, NCI Thesaurus) drug_type - type drug molecule (Antibody, small molecule etc) molecule_chembl_id - ChEMBL compound identifier drug_action_type - main action elicited drug (antagonist, inhibitor, stabiliser etc) drug_alias - collection unambiguous drug aliases (separated '|') nci_concept_definition - detailed description drug mechanism--action (NCI Thesaurus) opentargets - logical - drug found Open Targets Platform resource is_salt - logical - drug record represents salt form (excluded default) is_adc - logical - drug record represents antibody-drug conjugate (ADC - excluded default) drug_blacbox_warning - logical indicating drug blackbox warning nci_t - NCI thesaurus identifier target_symbol - gene symbol drug target target_entrezgene - Entrez gene identifier drug target target_genename - gene name/description drug target target_ensembl_gene_id - Ensembl gene identifier drug target target_type - type drug target (single protein, protein family etc.) drug_max_phase_indication - maximum clinical phase drug (given indication) drug_approved_indication - logical indicating drug approved indication drug_frac_cancer_indications - fraction drug indications cancers drug_approved_noncancer - logical indicating drug approved non-cancer disease drug_n_indications - number indications given drug (approved indications, clinical trials etc) drug_year_first_approval - year drug first approved drug_max_ct_phase - maximum clinical phase drug (indication) disease_efo_id - EFO (Experimental Factor Ontology) identifier drug indication disease_efo_label - EFO (Experimental Factor Ontology) label drug indication primary_site - primary tumor site/type (obtained https://github.com/sigven/oncoPhenoMap) drug_clinical_id - drug clinical identifier (clinicaltrials.gov, DailyMed, FDA etc.) drug_clinical_source - underlying source drug entry (DailyMed, clinicaltrials.gov, FDA etc.) atc_code_level1 - drug identifier ATC (level 1) atc_level1 - drug label ATC (level 1) atc_code_level1 - drug identifier ATC (level 2) atc_level2 - drug label ATC (level 2) atc_code_level3 - drug identifier ATC (level 3) atc_level3 - drug label ATC (level 3) atc_treatment_category - treatment category (targeted/chemo/hormone, cancer/etc)","code":""},{"path":"https://sigven.github.io/pharmOncoX/reference/get_targeted_drugs.html","id":null,"dir":"Reference","previous_headings":"","what":"Utility function to get on-label/off-label drugs (not complete) — get_targeted_drugs","title":"Utility function to get on-label/off-label drugs (not complete) — get_targeted_drugs","text":"Utility function get -label/-label drugs (complete)","code":""},{"path":"https://sigven.github.io/pharmOncoX/reference/get_targeted_drugs.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Utility function to get on-label/off-label drugs (not complete) — get_targeted_drugs","text":"","code":"get_targeted_drugs(cache_dir = NA)"},{"path":"https://sigven.github.io/pharmOncoX/reference/get_targeted_drugs.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Utility function to get on-label/off-label drugs (not complete) — get_targeted_drugs","text":"cache_dir Local cache directory","code":""},{"path":"https://sigven.github.io/pharmOncoX/reference/tidyeval.html","id":null,"dir":"Reference","previous_headings":"","what":"Tidy eval helpers — tidyeval","title":"Tidy eval helpers — tidyeval","text":"https://cran.r-project.org/web/packages/dplyr/vignettes/programming.html","code":""},{"path":"https://sigven.github.io/pharmOncoX/news/index.html","id":"version-156-january-31st-2024","dir":"Changelog","previous_headings":"","what":"Version 1.5.6 (January 31st 2024)","title":"Version 1.5.6 (January 31st 2024)","text":"Refine possible values treatment_category argument get_drugs() function Fix anti-androgen classification Fixed bug alias type notation copy numbers expression biomarkers Filter noise rank output helper function get_targeted_drugs Include variant primary name biomarker variants","code":""},{"path":"https://sigven.github.io/pharmOncoX/news/index.html","id":"version-150-january-25th-2024","dir":"Changelog","previous_headings":"","what":"Version 1.5.0 (January 25th 2024)","title":"Version 1.5.0 (January 25th 2024)","text":"Considerable improvement drug classifications (output column atc_level3), considering targeted agents chemotherapy argument drug_targeted_agent renamed treatment_category helper function get_on_off_label_drugs renamed get_targeted_drugs","code":""},{"path":"https://sigven.github.io/pharmOncoX/news/index.html","id":"version-1410-january-17th-2024","dir":"Changelog","previous_headings":"","what":"Version 1.4.10 (January 17th 2024)","title":"Version 1.4.10 (January 17th 2024)","text":"Updated NCI Thesaurus (23.12d) Updated CIViC data (20240114) Revised manual drug classification (building upon ATC)","code":""},{"path":"https://sigven.github.io/pharmOncoX/news/index.html","id":"version-148-december-12th-2023","dir":"Changelog","previous_headings":"","what":"Version 1.4.8 (December 12th 2023)","title":"Version 1.4.8 (December 12th 2023)","text":"Updated NCI Thesaurus - 23.11d Updated CIViC data (20231212)","code":""},{"path":"https://sigven.github.io/pharmOncoX/news/index.html","id":"version-148-november-30th-2023","dir":"Changelog","previous_headings":"","what":"Version 1.4.8 (November 30th 2023)","title":"Version 1.4.8 (November 30th 2023)","text":"Updated OTP (v2023.12) Updated Mitelman database (20231016)","code":""},{"path":"https://sigven.github.io/pharmOncoX/news/index.html","id":"version-147-november-3rd-2023","dir":"Changelog","previous_headings":"","what":"Version 1.4.7 (November 3rd 2023)","title":"Version 1.4.7 (November 3rd 2023)","text":"Fixed corrupt biomarker literature data frame","code":""},{"path":"https://sigven.github.io/pharmOncoX/news/index.html","id":"version-146-october-18th-2023","dir":"Changelog","previous_headings":"","what":"Version 1.4.6 (October 18th 2023)","title":"Version 1.4.6 (October 18th 2023)","text":"Fixed metadata Fixed -dated version descriptions (GH site) exclude compounds missing drug action type (platins etc.)","code":""},{"path":"https://sigven.github.io/pharmOncoX/news/index.html","id":"version-145-october-6th-2023","dir":"Changelog","previous_headings":"","what":"Version 1.4.5 (October 6th 2023)","title":"Version 1.4.5 (October 6th 2023)","text":"Updated NCI Thesaurus - 23.09d Updated CIViC data Added drug class (ATC) get_on_off_label_drugs()","code":""},{"path":"https://sigven.github.io/pharmOncoX/news/index.html","id":"version-144-september-1st-2023","dir":"Changelog","previous_headings":"","what":"Version 1.4.4 (September 1st 2023)","title":"Version 1.4.4 (September 1st 2023)","text":"Updated NCI Thesaurus - 23.08d Updated CIViC data Updated Mitelman database (20230803) get_biomarkers() now exported main function","code":""}]
biomarkers <- get_biomarkers( cache_dir = cache_dir) -#> INFO [2024-01-30 13:47:07] Downloading remote dataset from Google Drive to cache_dir -#> INFO [2024-01-30 13:47:11] Reading from cache_dir = ' (/tmp/RtmpHGxjPN'), argument force_download = F -#> INFO [2024-01-30 13:47:11] Object 'biomarkers' sucessfully loaded -#> INFO [2024-01-30 13:47:11] md5 checksum is valid: d3a942cfc0a999ad2d33610379ebd08b +#> INFO [2024-01-31 09:53:17] Downloading remote dataset from Google Drive to cache_dir +#> INFO [2024-01-31 09:53:20] Reading from cache_dir = ' (/tmp/RtmpsbEbNc'), argument force_download = F +#> INFO [2024-01-31 09:53:20] Object 'biomarkers' sucessfully loaded +#> INFO [2024-01-31 09:53:20] md5 checksum is valid: 98fcfe1b54c2b393112c0be81e58fc9e brca1_biomarkers <- list() for(source in c('civic','cgi')){ @@ -617,8 +617,8 @@ R dom = "Bfrtip") )
Source: inst/CITATION
inst/CITATION
Nakken S. (2023) pharmOncoX: Targeted and non-targeted anti-cancer drugs and drug regimens. R package version 1.5.5. (https://github.com/sigven/pharmOncoX)
Nakken S. (2023) pharmOncoX: Targeted and non-targeted anti-cancer drugs and drug regimens. R package version 1.5.6. (https://github.com/sigven/pharmOncoX)
@Manual{, title = {pharmOncoX: Targeted and non-targeted anti-cancer drugs and drug regimens}, author = {Sigve Nakken}, year = {2023}, - note = {R package version 1.5.5}, + note = {R package version 1.5.6}, url = {https://github.com/sigven/pharmOncoX}, }
treatment_category
get_drugs()
get_targeted_drugs