README.md
In LiNk-NY/oncoKBData: A package to access the oncoKB web API
oncoKBData
The aim of the package is to expose the OncoKB API through an R client.
This vignette demonstrates public API access. To learn more about the
OncoKB database, visit https://www.oncokb.org.
Installation
To get the development version of oncoKBData use:
if (!requireNamespace("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("waldronlab/oncoKBData")
Package Load
library(oncoKBData)
library(S4Vectors)
Introduction
The oncoKBData aims to provide access to the OncoKB API via the public
API. Access is also possible with a licensed token.
API representation
In order to use the OncoKB API, we must instantiate an API object as
provided by the
rapiclient and
AnVIL packages.
oncokb <- oncoKB()
Note that for private API access, users must change the api. argument
in the oncoKB function.
Operations
Check available tags, operations, and descriptions as a tibble:
tags(oncokb)
#> # A tibble: 20 × 3
#> tag operation summary
#> <chr> <chr> <chr>
#> 1 Annotations annotateCopyNumberAlterationsGetUsingGET_1 annotateCopyNumberAlterationsGet
#> 2 Annotations annotateCopyNumberAlterationsPostUsingPOST_1 annotateCopyNumberAlterationsPost
#> 3 Annotations annotateMutationsByGenomicChangeGetUsingGET_1 annotateMutationsByGenomicChangeGet
#> 4 Annotations annotateMutationsByGenomicChangePostUsingPOST_1 annotateMutationsByGenomicChangePost
#> 5 Annotations annotateMutationsByHGVSgGetUsingGET_1 annotateMutationsByHGVSgGet
#> 6 Annotations annotateMutationsByHGVSgPostUsingPOST_1 annotateMutationsByHGVSgPost
#> 7 Annotations annotateMutationsByProteinChangeGetUsingGET_1 annotateMutationsByProteinChangeGet
#> 8 Annotations annotateMutationsByProteinChangePostUsingPOST_1 annotateMutationsByProteinChangePost
#> 9 Annotations annotateStructuralVariantsGetUsingGET_1 annotateStructuralVariantsGet
#> 10 Annotations annotateStructuralVariantsPostUsingPOST_1 annotateStructuralVariantsPost
#> 11 Cancer Genes utilsAllCuratedGenesGetUsingGET_1 utilsAllCuratedGenesGet
#> 12 Cancer Genes utilsAllCuratedGenesTxtGetUsingGET_1 utilsAllCuratedGenesTxtGet
#> 13 Cancer Genes utilsCancerGeneListGetUsingGET_1 utilsCancerGeneListGet
#> 14 Cancer Genes utilsCancerGeneListTxtGetUsingGET_1 utilsCancerGeneListTxtGet
#> 15 Info infoGetUsingGET_1 infoGet
#> 16 Levels levelsDiagnosticGetUsingGET_1 levelsDiagnosticGet
#> 17 Levels levelsGetUsingGET_1 levelsGet
#> 18 Levels levelsPrognosticGetUsingGET_1 levelsPrognosticGet
#> 19 Levels levelsResistanceGetUsingGET_1 levelsResistanceGet
#> 20 Levels levelsSensitiveGetUsingGET_1 levelsSensitiveGet
head(tags(oncokb)$operation)
#> [1] "annotateCopyNumberAlterationsGetUsingGET_1" "annotateCopyNumberAlterationsPostUsingPOST_1"
#> [3] "annotateMutationsByGenomicChangeGetUsingGET_1" "annotateMutationsByGenomicChangePostUsingPOST_1"
#> [5] "annotateMutationsByHGVSgGetUsingGET_1" "annotateMutationsByHGVSgPostUsingPOST_1"
Note. The annotations API access requires a token.
Levels of Evidence
To retrieve the levels of evidence for all types (i.e., ‘therapeutic’,
‘diagnostic’, ‘prognostic’, and ‘FDA’) run the levelsOfEvidence
function.
(loe <- levelsOfEvidence(oncokb))
#> DataFrame with 16 rows and 4 columns
#> levelOfEvidence description htmlDescription colorHex
#> <character> <character> <character> <character>
#> 1 LEVEL_1 FDA-recognized bioma.. <span><b>FDA-recogni.. #33A02C
#> 2 LEVEL_2 Standard care biomar.. <span><b>Standard ca.. #1F78B4
#> 3 LEVEL_3A Compelling clinical .. <span><b>Compelling .. #984EA3
#> 4 LEVEL_3B Standard care or inv.. <span><b>Standard ca.. #BE98CE
#> 5 LEVEL_4 Compelling biologica.. <span><b>Compelling .. #424242
#> ... ... ... ... ...
#> 12 LEVEL_Px1 FDA and/or professio.. <span><b>FDA and/or .. #33A02C
#> 13 LEVEL_Px2 FDA and/or professio.. <span><b>FDA and/or .. #1F78B4
#> 14 LEVEL_Px3 Biomarker is prognos.. <span>Biomarker is p.. #984EA3
#> 15 LEVEL_R1 Standard care biomar.. <span><b>Standard of.. #EE3424
#> 16 LEVEL_R2 Compelling clinical .. <span><b>Compelling .. #F79A92
It will return a DataFrame with important metadata:
names(metadata(loe))
#> [1] "oncoTreeVersion" "ncitVersion" "dataVersion" "appVersion" "apiVersion" "publicInstance"
metadata(loe)["oncoTreeVersion"]
#> $oncoTreeVersion
#> [1] "oncotree_2019_12_01"
metadata(loe)[["apiVersion"]]
#> $version
#> [1] "v1.4.0"
#>
#> $major
#> [1] 1
#>
#> $minor
#> [1] 4
#>
#> $patch
#> [1] 0
#>
#> $suffixTokens
#> list()
#>
#> $stable
#> [1] TRUE
Gene tables
The API allows retrieval of curated genes where there is a single gene
per observation:
curatedGenes(oncokb)
#> # A tibble: 725 × 13
#> grch37Isoform grch37RefSeq grch38Isoform grch38RefSeq entrezGeneId hugoSymbol oncogene highest…¹ highe…² summary backg…³ tsg highe…⁴
#> <chr> <chr> <chr> <chr> <int> <chr> <lgl> <chr> <chr> <chr> <chr> <lgl> <chr>
#> 1 ENST00000318560 NM_005157.4 ENST00000318560 NM_005157.4 25 ABL1 TRUE "1" "R1" ABL1, … "ABL1 … FALSE "R1"
#> 2 ENST00000502732 NM_007314.3 ENST00000502732 NM_007314.3 27 ABL2 TRUE "" "" ABL2, … "ABL2 … FALSE ""
#> 3 ENST00000321945 NM_139076.2 ENST00000321945 NM_139076.2 84142 ABRAXAS1 FALSE "" "" ABRAXA… "The A… TRUE ""
#> 4 ENST00000331925 NM_001199954.1 ENST00000573283 NM_001199954.1 71 ACTG1 FALSE "" "" ACTG1,… "ACTG1… TRUE ""
#> 5 ENST00000263640 NM_001111067.2 ENST00000263640 NM_001111067.2 90 ACVR1 TRUE "" "" ACVR1,… "ACVR1… FALSE ""
#> 6 ENST00000396623 NM_144650 ENST00000396623 NM_144650 137872 ADHFE1 TRUE "" "" ADHFE1… "ADHFE… FALSE ""
#> 7 ENST00000265343 NM_014423 ENST00000265343 NM_014423 27125 AFF4 TRUE "" "" AFF4, … "AFF4 … FALSE ""
#> 8 ENST00000373204 NM_012199.2 ENST00000373204 NM_012199.2 26523 AGO1 TRUE "" "" AGO1, … "AGO1 … FALSE ""
#> 9 ENST00000220592 NM_012154.3 ENST00000220592 NM_012154.3 27161 AGO2 FALSE "" "" AGO2, … "AGO2 … FALSE ""
#> 10 ENST00000262713 NM_032876.5 ENST00000262713 NM_032876.5 84962 AJUBA FALSE "" "" AJUBA,… "AJUBA… TRUE ""
#> # … with 715 more rows, and abbreviated variable names ¹highestSensitiveLevel, ²highestResistanceLevel, ³background, ⁴highestResistancLevel
and a long list of genes associated with cancer where there can be
multiple entries for the same hugoSymbol due to multiple
geneAliases:
cancerGeneList(oncokb)
#> # A tibble: 3,019 × 17
#> hugoSymbol entrezGeneId grch37…¹ grch3…² grch3…³ grch3…⁴ oncok…⁵ occur…⁶ mSKIm…⁷ mSKHeme found…⁸ found…⁹ vogel…˟ sange…˟ geneA…˟ tsg oncog…˟
#> <chr> <int> <chr> <chr> <chr> <chr> <lgl> <int> <lgl> <lgl> <lgl> <lgl> <lgl> <lgl> <list> <lgl> <lgl>
#> 1 ABL1 25 ENST000… NM_005… ENST00… NM_005… TRUE 7 TRUE TRUE TRUE TRUE TRUE TRUE <chr> FALSE TRUE
#> 2 ABL1 25 ENST000… NM_005… ENST00… NM_005… TRUE 7 TRUE TRUE TRUE TRUE TRUE TRUE <chr> FALSE TRUE
#> 3 ABL1 25 ENST000… NM_005… ENST00… NM_005… TRUE 7 TRUE TRUE TRUE TRUE TRUE TRUE <chr> FALSE TRUE
#> 4 AKT1 207 ENST000… NM_001… ENST00… NM_001… TRUE 7 TRUE TRUE TRUE TRUE TRUE TRUE <chr> FALSE TRUE
#> 5 AKT1 207 ENST000… NM_001… ENST00… NM_001… TRUE 7 TRUE TRUE TRUE TRUE TRUE TRUE <chr> FALSE TRUE
#> 6 AKT1 207 ENST000… NM_001… ENST00… NM_001… TRUE 7 TRUE TRUE TRUE TRUE TRUE TRUE <chr> FALSE TRUE
#> 7 AKT1 207 ENST000… NM_001… ENST00… NM_001… TRUE 7 TRUE TRUE TRUE TRUE TRUE TRUE <chr> FALSE TRUE
#> 8 AKT1 207 ENST000… NM_001… ENST00… NM_001… TRUE 7 TRUE TRUE TRUE TRUE TRUE TRUE <chr> FALSE TRUE
#> 9 ALK 238 ENST000… NM_004… ENST00… NM_004… TRUE 7 TRUE TRUE TRUE TRUE TRUE TRUE <chr> FALSE TRUE
#> 10 AMER1 139285 ENST000… NM_152… ENST00… NM_152… TRUE 7 TRUE TRUE TRUE TRUE TRUE TRUE <chr> TRUE FALSE
#> # … with 3,009 more rows, and abbreviated variable names ¹grch37Isoform, ²grch37RefSeq, ³grch38Isoform, ⁴grch38RefSeq, ⁵oncokbAnnotated,
#> # ⁶occurrenceCount, ⁷mSKImpact, ⁸foundation, ⁹foundationHeme, ˟vogelstein, ˟sangerCGC, ˟geneAliases, ˟oncogene
Session Information
sessionInfo()
#> R Under development (unstable) (2023-02-22 r83892)
#> Platform: x86_64-pc-linux-gnu (64-bit)
#> Running under: Ubuntu 22.04.1 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=en_US.UTF-8 LC_NUMERIC=C LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8 LC_MONETARY=en_US.UTF-8
#> [6] LC_MESSAGES=en_US.UTF-8 LC_PAPER=en_US.UTF-8 LC_NAME=C LC_ADDRESS=C LC_TELEPHONE=C
#> [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
#>
#> time zone: Etc/UTC
#> tzcode source: system (glibc)
#>
#> attached base packages:
#> [1] stats4 stats graphics grDevices utils datasets methods base
#>
#> other attached packages:
#> [1] BiocStyle_2.27.1 S4Vectors_0.37.4 BiocGenerics_0.45.0 oncoKBData_0.99.1 AnVIL_1.11.3 dplyr_1.1.0 colorout_1.2-2
#>
#> loaded via a namespace (and not attached):
#> [1] utf8_1.2.3 generics_0.1.3 tidyr_1.3.0 futile.options_1.0.1 digest_0.6.31 magrittr_2.0.3
#> [7] evaluate_0.20 fastmap_1.1.1 jsonlite_1.8.4 DBI_1.1.3 formatR_1.14 promises_1.2.0.1
#> [13] BiocManager_1.30.20 httr_1.4.5 purrr_1.0.1 fansi_1.0.4 rapiclient_0.1.3 codetools_0.2-19
#> [19] cli_3.6.0 shiny_1.7.4 rlang_1.0.6 futile.logger_1.4.3 ellipsis_0.3.2 withr_2.5.0
#> [25] yaml_2.3.7 tools_4.3.0 parallel_4.3.0 httpuv_1.6.9 DT_0.27 lambda.r_1.2.4
#> [31] curl_5.0.0 vctrs_0.5.2 R6_2.5.1 mime_0.12 lifecycle_1.0.3 htmlwidgets_1.6.1
#> [37] miniUI_0.1.1.1 pkgconfig_2.0.3 pillar_1.8.1 later_1.3.0 glue_1.6.2 Rcpp_1.0.10
#> [43] xfun_0.37 tibble_3.1.8 tidyselect_1.2.0 rstudioapi_0.14 knitr_1.42 xtable_1.8-4
#> [49] htmltools_0.5.4 rmarkdown_2.20 compiler_4.3.0
LiNk-NY/oncoKBData documentation built on Oct. 1, 2024, 1:57 p.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
oncoKBData
The aim of the package is to expose the OncoKB API through an R client. This vignette demonstrates public API access. To learn more about the OncoKB database, visit https://www.oncokb.org.
Installation
To get the development version of oncoKBData use:
if (!requireNamespace("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("waldronlab/oncoKBData")
Package Load
library(oncoKBData)
library(S4Vectors)
Introduction
The oncoKBData aims to provide access to the OncoKB API via the public
API. Access is also possible with a licensed token.
API representation
In order to use the OncoKB API, we must instantiate an API object as provided by the rapiclient and AnVIL packages.
oncokb <- oncoKB()
Note that for private API access, users must change the api. argument
in the oncoKB function.
Operations
Check available tags, operations, and descriptions as a tibble:
tags(oncokb)
#> # A tibble: 20 × 3
#> tag operation summary
#> <chr> <chr> <chr>
#> 1 Annotations annotateCopyNumberAlterationsGetUsingGET_1 annotateCopyNumberAlterationsGet
#> 2 Annotations annotateCopyNumberAlterationsPostUsingPOST_1 annotateCopyNumberAlterationsPost
#> 3 Annotations annotateMutationsByGenomicChangeGetUsingGET_1 annotateMutationsByGenomicChangeGet
#> 4 Annotations annotateMutationsByGenomicChangePostUsingPOST_1 annotateMutationsByGenomicChangePost
#> 5 Annotations annotateMutationsByHGVSgGetUsingGET_1 annotateMutationsByHGVSgGet
#> 6 Annotations annotateMutationsByHGVSgPostUsingPOST_1 annotateMutationsByHGVSgPost
#> 7 Annotations annotateMutationsByProteinChangeGetUsingGET_1 annotateMutationsByProteinChangeGet
#> 8 Annotations annotateMutationsByProteinChangePostUsingPOST_1 annotateMutationsByProteinChangePost
#> 9 Annotations annotateStructuralVariantsGetUsingGET_1 annotateStructuralVariantsGet
#> 10 Annotations annotateStructuralVariantsPostUsingPOST_1 annotateStructuralVariantsPost
#> 11 Cancer Genes utilsAllCuratedGenesGetUsingGET_1 utilsAllCuratedGenesGet
#> 12 Cancer Genes utilsAllCuratedGenesTxtGetUsingGET_1 utilsAllCuratedGenesTxtGet
#> 13 Cancer Genes utilsCancerGeneListGetUsingGET_1 utilsCancerGeneListGet
#> 14 Cancer Genes utilsCancerGeneListTxtGetUsingGET_1 utilsCancerGeneListTxtGet
#> 15 Info infoGetUsingGET_1 infoGet
#> 16 Levels levelsDiagnosticGetUsingGET_1 levelsDiagnosticGet
#> 17 Levels levelsGetUsingGET_1 levelsGet
#> 18 Levels levelsPrognosticGetUsingGET_1 levelsPrognosticGet
#> 19 Levels levelsResistanceGetUsingGET_1 levelsResistanceGet
#> 20 Levels levelsSensitiveGetUsingGET_1 levelsSensitiveGet
head(tags(oncokb)$operation)
#> [1] "annotateCopyNumberAlterationsGetUsingGET_1" "annotateCopyNumberAlterationsPostUsingPOST_1"
#> [3] "annotateMutationsByGenomicChangeGetUsingGET_1" "annotateMutationsByGenomicChangePostUsingPOST_1"
#> [5] "annotateMutationsByHGVSgGetUsingGET_1" "annotateMutationsByHGVSgPostUsingPOST_1"
Note. The annotations API access requires a token.
Levels of Evidence
To retrieve the levels of evidence for all types (i.e., ‘therapeutic’,
‘diagnostic’, ‘prognostic’, and ‘FDA’) run the levelsOfEvidence
function.
(loe <- levelsOfEvidence(oncokb))
#> DataFrame with 16 rows and 4 columns
#> levelOfEvidence description htmlDescription colorHex
#> <character> <character> <character> <character>
#> 1 LEVEL_1 FDA-recognized bioma.. <span><b>FDA-recogni.. #33A02C
#> 2 LEVEL_2 Standard care biomar.. <span><b>Standard ca.. #1F78B4
#> 3 LEVEL_3A Compelling clinical .. <span><b>Compelling .. #984EA3
#> 4 LEVEL_3B Standard care or inv.. <span><b>Standard ca.. #BE98CE
#> 5 LEVEL_4 Compelling biologica.. <span><b>Compelling .. #424242
#> ... ... ... ... ...
#> 12 LEVEL_Px1 FDA and/or professio.. <span><b>FDA and/or .. #33A02C
#> 13 LEVEL_Px2 FDA and/or professio.. <span><b>FDA and/or .. #1F78B4
#> 14 LEVEL_Px3 Biomarker is prognos.. <span>Biomarker is p.. #984EA3
#> 15 LEVEL_R1 Standard care biomar.. <span><b>Standard of.. #EE3424
#> 16 LEVEL_R2 Compelling clinical .. <span><b>Compelling .. #F79A92
It will return a DataFrame with important metadata:
names(metadata(loe))
#> [1] "oncoTreeVersion" "ncitVersion" "dataVersion" "appVersion" "apiVersion" "publicInstance"
metadata(loe)["oncoTreeVersion"]
#> $oncoTreeVersion
#> [1] "oncotree_2019_12_01"
metadata(loe)[["apiVersion"]]
#> $version
#> [1] "v1.4.0"
#>
#> $major
#> [1] 1
#>
#> $minor
#> [1] 4
#>
#> $patch
#> [1] 0
#>
#> $suffixTokens
#> list()
#>
#> $stable
#> [1] TRUE
Gene tables
The API allows retrieval of curated genes where there is a single gene per observation:
curatedGenes(oncokb)
#> # A tibble: 725 × 13
#> grch37Isoform grch37RefSeq grch38Isoform grch38RefSeq entrezGeneId hugoSymbol oncogene highest…¹ highe…² summary backg…³ tsg highe…⁴
#> <chr> <chr> <chr> <chr> <int> <chr> <lgl> <chr> <chr> <chr> <chr> <lgl> <chr>
#> 1 ENST00000318560 NM_005157.4 ENST00000318560 NM_005157.4 25 ABL1 TRUE "1" "R1" ABL1, … "ABL1 … FALSE "R1"
#> 2 ENST00000502732 NM_007314.3 ENST00000502732 NM_007314.3 27 ABL2 TRUE "" "" ABL2, … "ABL2 … FALSE ""
#> 3 ENST00000321945 NM_139076.2 ENST00000321945 NM_139076.2 84142 ABRAXAS1 FALSE "" "" ABRAXA… "The A… TRUE ""
#> 4 ENST00000331925 NM_001199954.1 ENST00000573283 NM_001199954.1 71 ACTG1 FALSE "" "" ACTG1,… "ACTG1… TRUE ""
#> 5 ENST00000263640 NM_001111067.2 ENST00000263640 NM_001111067.2 90 ACVR1 TRUE "" "" ACVR1,… "ACVR1… FALSE ""
#> 6 ENST00000396623 NM_144650 ENST00000396623 NM_144650 137872 ADHFE1 TRUE "" "" ADHFE1… "ADHFE… FALSE ""
#> 7 ENST00000265343 NM_014423 ENST00000265343 NM_014423 27125 AFF4 TRUE "" "" AFF4, … "AFF4 … FALSE ""
#> 8 ENST00000373204 NM_012199.2 ENST00000373204 NM_012199.2 26523 AGO1 TRUE "" "" AGO1, … "AGO1 … FALSE ""
#> 9 ENST00000220592 NM_012154.3 ENST00000220592 NM_012154.3 27161 AGO2 FALSE "" "" AGO2, … "AGO2 … FALSE ""
#> 10 ENST00000262713 NM_032876.5 ENST00000262713 NM_032876.5 84962 AJUBA FALSE "" "" AJUBA,… "AJUBA… TRUE ""
#> # … with 715 more rows, and abbreviated variable names ¹highestSensitiveLevel, ²highestResistanceLevel, ³background, ⁴highestResistancLevel
and a long list of genes associated with cancer where there can be
multiple entries for the same hugoSymbol due to multiple
geneAliases:
cancerGeneList(oncokb)
#> # A tibble: 3,019 × 17
#> hugoSymbol entrezGeneId grch37…¹ grch3…² grch3…³ grch3…⁴ oncok…⁵ occur…⁶ mSKIm…⁷ mSKHeme found…⁸ found…⁹ vogel…˟ sange…˟ geneA…˟ tsg oncog…˟
#> <chr> <int> <chr> <chr> <chr> <chr> <lgl> <int> <lgl> <lgl> <lgl> <lgl> <lgl> <lgl> <list> <lgl> <lgl>
#> 1 ABL1 25 ENST000… NM_005… ENST00… NM_005… TRUE 7 TRUE TRUE TRUE TRUE TRUE TRUE <chr> FALSE TRUE
#> 2 ABL1 25 ENST000… NM_005… ENST00… NM_005… TRUE 7 TRUE TRUE TRUE TRUE TRUE TRUE <chr> FALSE TRUE
#> 3 ABL1 25 ENST000… NM_005… ENST00… NM_005… TRUE 7 TRUE TRUE TRUE TRUE TRUE TRUE <chr> FALSE TRUE
#> 4 AKT1 207 ENST000… NM_001… ENST00… NM_001… TRUE 7 TRUE TRUE TRUE TRUE TRUE TRUE <chr> FALSE TRUE
#> 5 AKT1 207 ENST000… NM_001… ENST00… NM_001… TRUE 7 TRUE TRUE TRUE TRUE TRUE TRUE <chr> FALSE TRUE
#> 6 AKT1 207 ENST000… NM_001… ENST00… NM_001… TRUE 7 TRUE TRUE TRUE TRUE TRUE TRUE <chr> FALSE TRUE
#> 7 AKT1 207 ENST000… NM_001… ENST00… NM_001… TRUE 7 TRUE TRUE TRUE TRUE TRUE TRUE <chr> FALSE TRUE
#> 8 AKT1 207 ENST000… NM_001… ENST00… NM_001… TRUE 7 TRUE TRUE TRUE TRUE TRUE TRUE <chr> FALSE TRUE
#> 9 ALK 238 ENST000… NM_004… ENST00… NM_004… TRUE 7 TRUE TRUE TRUE TRUE TRUE TRUE <chr> FALSE TRUE
#> 10 AMER1 139285 ENST000… NM_152… ENST00… NM_152… TRUE 7 TRUE TRUE TRUE TRUE TRUE TRUE <chr> TRUE FALSE
#> # … with 3,009 more rows, and abbreviated variable names ¹grch37Isoform, ²grch37RefSeq, ³grch38Isoform, ⁴grch38RefSeq, ⁵oncokbAnnotated,
#> # ⁶occurrenceCount, ⁷mSKImpact, ⁸foundation, ⁹foundationHeme, ˟vogelstein, ˟sangerCGC, ˟geneAliases, ˟oncogene
Session Information
sessionInfo()
#> R Under development (unstable) (2023-02-22 r83892)
#> Platform: x86_64-pc-linux-gnu (64-bit)
#> Running under: Ubuntu 22.04.1 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=en_US.UTF-8 LC_NUMERIC=C LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8 LC_MONETARY=en_US.UTF-8
#> [6] LC_MESSAGES=en_US.UTF-8 LC_PAPER=en_US.UTF-8 LC_NAME=C LC_ADDRESS=C LC_TELEPHONE=C
#> [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
#>
#> time zone: Etc/UTC
#> tzcode source: system (glibc)
#>
#> attached base packages:
#> [1] stats4 stats graphics grDevices utils datasets methods base
#>
#> other attached packages:
#> [1] BiocStyle_2.27.1 S4Vectors_0.37.4 BiocGenerics_0.45.0 oncoKBData_0.99.1 AnVIL_1.11.3 dplyr_1.1.0 colorout_1.2-2
#>
#> loaded via a namespace (and not attached):
#> [1] utf8_1.2.3 generics_0.1.3 tidyr_1.3.0 futile.options_1.0.1 digest_0.6.31 magrittr_2.0.3
#> [7] evaluate_0.20 fastmap_1.1.1 jsonlite_1.8.4 DBI_1.1.3 formatR_1.14 promises_1.2.0.1
#> [13] BiocManager_1.30.20 httr_1.4.5 purrr_1.0.1 fansi_1.0.4 rapiclient_0.1.3 codetools_0.2-19
#> [19] cli_3.6.0 shiny_1.7.4 rlang_1.0.6 futile.logger_1.4.3 ellipsis_0.3.2 withr_2.5.0
#> [25] yaml_2.3.7 tools_4.3.0 parallel_4.3.0 httpuv_1.6.9 DT_0.27 lambda.r_1.2.4
#> [31] curl_5.0.0 vctrs_0.5.2 R6_2.5.1 mime_0.12 lifecycle_1.0.3 htmlwidgets_1.6.1
#> [37] miniUI_0.1.1.1 pkgconfig_2.0.3 pillar_1.8.1 later_1.3.0 glue_1.6.2 Rcpp_1.0.10
#> [43] xfun_0.37 tibble_3.1.8 tidyselect_1.2.0 rstudioapi_0.14 knitr_1.42 xtable_1.8-4
#> [49] htmltools_0.5.4 rmarkdown_2.20 compiler_4.3.0
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