Package: DeepTarget 0.99.19

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. We also guided how to interpret the result.

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

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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'))

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-0.99.19(bioc 3.20)

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

bioconductor-package

11 exports 1.31 score 140 dependencies

Last updated 3 months agofrom:c151b95a6d

Exports:computeCor Depmap2DeepTarget DMB DoInteractExp DoInteractMutant DoPWY DTR plotCor plotSim PredMaxSim PredTarget

Dependencies:abind AnnotationDbi AnnotationHub askpass backports BH Biobase BiocFileCache BiocGenerics BiocManager BiocParallel BiocVersion Biostrings bit bit64 blob boot brio broom cachem callr car carData cli clipr codetools colorspace corrplot cowplot cpp11 crayon curl data.table DBI dbplyr depmap desc diffobj digest dplyr evaluate ExperimentHub fansi farver fastmap fastmatch fgsea filelock formatR fs futile.logger futile.options generics GenomeInfoDb GenomeInfoDbData ggplot2 ggpubr ggrepel ggsci ggsignif glue gridExtra gtable hms httr httr2 IRanges isoband jsonlite KEGGREST labeling lambda.r lattice lifecycle lme4 magrittr MASS Matrix MatrixModels memoise mgcv mime minqa munsell nlme nloptr nnet numDeriv openssl pbkrtest pillar pkgbuild pkgconfig pkgload plogr plyr png polynom praise prettyunits pROC processx progress ps purrr quantreg R6 rappdirs RColorBrewer Rcpp RcppEigen readr rematch2 rlang rprojroot RSQLite rstatix S4Vectors scales snow SparseM stringi stringr survival sys testthat tibble tidyr tidyselect tzdb UCSC.utils utf8 vctrs viridisLite vroom waldo withr XVector yaml zlibbioc

Workflow Demonstration for Deep characterization of cancer drugs

Rendered fromDeepTarget_Vignette.Rmdusingknitr::rmarkdownon Jun 13 2024.

Last update: 2024-04-23
Started: 2023-11-30

Help page	Topics
Compute a correlation between the every gene vs each drug response	computeCor
Retrieval and preparation of input data required from Depmap to Deeptarget package.	Depmap2DeepTarget
Predicting Drug Mutant Binding for mutant or non-mutant form	DMB
Compute the interaction between the drug and KO expression	DoInteractExp
Compute interaction between the drug and KO expression in term of mutant vs non-mutant	DoInteractMutant
Provide a probability score for each pathway for the primary of mechanism of action (MOA) of a drug	DoPWY
Predicting Drug Target Response (DTR) for primary or secondary targets	DTR
An object containing a small part of the data from the Cancer Dependency Map (depmap.org) to demonstrate in DeepTarget pipeline	OntargetM
Plot the correlation	plotCor
Plot the similarty between corelation values and P vals for all genes. The top 5 genes are labeled.	plotSim
Predict the most similar gene to the drug response	PredMaxSim
Prediction of the most similar known targeted gene.	PredTarget

Package: DeepTarget 0.99.19

DeepTarget: Deep characterization of cancer drugs

Workflow Demonstration for Deep characterization of cancer drugs

Citation

Development and contributors

Readme and manuals

Help Manual

Usage by other packages (reverse dependencies)