DESCRIPTION

Package: pgxBioc2022Workshop
Title: PharmacoGx 3.1: data structures and methods for discovering molecular biomarkers of response to drug combination therapy in precision oncology
Version: 1.0.9
Authors@R: c(
    person(
        given="Christopher",
        family="Eeles",
        email="christopher.eeles@uhnresearch.ca",
        role = c("aut"),
        comment = c(ORCID="0000-0002-9962-7385")),
    person(
        given="Petr",
        family="Smirnov",
        email="petr.smirnov@utoronto.ca",
        role=c("aut")),
    person(
        given="Feifei",
        family="Li",
        email="ff.li@mail.utoronto.ca",
        role=c("aut")),
    person(
        given="Benjamin",
        family="Haibe-Kains",
        email="benjamin.haibe.kains@utoronto.ca",
        role=c("aut", "cre"))
    )
Description: This workshop will introduce users to the CoreGx and PharmacoGx R
    packages, which are useful tools for pharmacogenomic modelling to discover
    biomarkers of treatment response in cancer model systems. PharmacoGx
    specifically focuses on drug sensitivity experiments in cancer cell lines,
    which will be the major focus of this workshop. Recent updates to PharmacoGx have
    added support for analyzing drug combination experiments to discover molecular biomarkers
    of drug synergy or antagonism. In this workshop users will learn how to use CoreGx and
    PharmacoGx to build a PharmacoSet object from cancer cell-lines with both their molecular
    phenotype and response to drug combination therapy characterized. This object will then be used
    to compute common metrics of drug synergy and antagonism and to use available molecular
    data to discover genes associated with response or resistance to both mono and drug combination
    therapies.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.2.0
Imports:
    CoreGx,
    PharmacoGx,
    MultiAssayExperiment,
    data.table
Suggests:
    knitr,
    rmarkdown,
    BiocStyle,
    pkgdown
Remotes:
    bhklab/CoreGx@development,
    bhklab/PharmacoGx@development
URL: https://bhklab.github.io/bioc2022workshop
VignetteBuilder: knitr
DockerImage: ghcr.io/bhklab/pgxBioc2022Workshop:latest