Package: DeepTarget 1.1.0

Trinh Nguyen

DeepTarget: Deep characterization of cancer drugs

This package predicts a drug’s primary target(s) or secondary target(s) by integrating large-scale genetic and drug screens from the Cancer Dependency Map project run by the Broad Institute. It further investigates whether the drug specifically targets the wild-type or mutated target forms. To show how to use this package in practice, we provided sample data along with step-by-step example.

Authors:Sanju Sinha [aut], Trinh Nguyen [aut, cre], Ying Hu [aut]

DeepTarget_1.1.0.tar.gz
DeepTarget_1.1.0.zip(r-4.5)DeepTarget_1.1.0.zip(r-4.4)
DeepTarget_1.1.0.tgz(r-4.4-any)
DeepTarget_1.1.0.tar.gz(r-4.5-noble)DeepTarget_1.1.0.tar.gz(r-4.4-noble)
DeepTarget_1.1.0.tgz(r-4.4-emscripten)
DeepTarget.pdf |DeepTarget.html
DeepTarget/json (API)
NEWS

# Install 'DeepTarget' in R:
install.packages('DeepTarget', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Datasets:
  • OntargetM - An object containing a small part of the data from the Cancer Dependency Map (depmap.org) to demonstrate in DeepTarget pipeline

On BioConductor:DeepTarget-1.1.0(bioc 3.21)DeepTarget-1.0.0(bioc 3.20)

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

genetargetgenepredictionpathwaysgeneexpressionrnaseqimmunooncologydifferentialexpressiongenesetenrichmentreportwritingcrispr

4.65 score 1 scripts 121 downloads 11 exports 129 dependencies

Last updated 2 months agofrom:3398b5df86. Checks:OK: 1 NOTE: 4. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 29 2024
R-4.5-winNOTENov 29 2024
R-4.5-linuxNOTENov 29 2024
R-4.4-winNOTENov 29 2024
R-4.4-macNOTENov 29 2024

Exports:computeCorDepmap2DeepTargetDMBDoInteractExpDoInteractMutantDoPWYDTRplotCorplotSimPredMaxSimPredTarget

Dependencies:abindAnnotationDbiAnnotationHubaskpassbackportsBHBiobaseBiocFileCacheBiocGenericsBiocManagerBiocParallelBiocVersionBiostringsbitbit64blobbootbroomcachemcarcarDataclicliprcodetoolscolorspacecorrplotcowplotcpp11crayoncurldata.tableDBIdbplyrdepmapDerivdoBydplyrExperimentHubfansifarverfastmapfastmatchfgseafilelockformatRFormulafutile.loggerfutile.optionsgenericsGenomeInfoDbGenomeInfoDbDataggplot2ggpubrggrepelggsciggsignifgluegridExtragtablehmshttrhttr2IRangesisobandjsonliteKEGGRESTlabelinglambda.rlatticelifecyclelme4magrittrMASSMatrixMatrixModelsmemoisemgcvmicrobenchmarkmimeminqamodelrmunsellnlmenloptrnnetnumDerivopensslpbkrtestpillarpkgconfigplogrplyrpngpolynomprettyunitspROCprogresspurrrquantregR6rappdirsRColorBrewerRcppRcppEigenreadrrlangRSQLiterstatixS4VectorsscalessnowSparseMstringistringrsurvivalsystibbletidyrtidyselecttzdbUCSC.utilsutf8vctrsviridisLitevroomwithrXVectoryamlzlibbioc

Workflow Demonstration for Deep characterization of cancer drugs

Rendered fromDeepTarget_Vignette.Rmdusingknitr::rmarkdownon Nov 29 2024.

Last update: 2024-10-21
Started: 2023-11-30