## ----style, eval=TRUE, echo=FALSE, results="asis"--------------------------
BiocStyle::latex()
## ----options, results='hide', message=FALSE, eval=TRUE, echo=FALSE---------
library(Xeva)
## ----get_lib, results='hide', message=FALSE, eval=FALSE--------------------
# if (!requireNamespace("BiocManager", quietly = TRUE))
# install.packages("BiocManager")
# BiocManager::install("Xeva", version = "3.8")
## ----githubInst, results='hide', message=FALSE, eval=FALSE-----------------
# #install devtools if required
# install.packages("devtools")
#
# #install Xeva as:
# devtools::install_github("bhklab/Xeva")
## ----l, results='hide', message=FALSE, eval=TRUE---------------------------
library(Xeva)
## ----biobase, results='hide', message=FALSE, eval=TRUE, echo=FALSE---------
suppressMessages(library(Biobase))
## ----l2--------------------------------------------------------------------
data(brca)
print(brca)
## ----l3--------------------------------------------------------------------
brca.mod <- modelInfo(brca)
dim(brca.mod)
brca.mod[1:4, ]
## ----expre-----------------------------------------------------------------
model.data <- getExperiment(brca, model.id = "X.1004.BG98")
head(model.data)
## ----batch1----------------------------------------------------------------
batch.name <- batchInfo(brca)
batch.name[1:4]
## ----batch2----------------------------------------------------------------
batchInfo(brca, batch = "X-1004.binimetinib")
## ----plot1, fig.cap="Tumor growth curves for a batch of control and treated PDXs", out.width='4in', fig.wide=TRUE----
plotPDX(brca, batch = "X-4567.BKM120")
## ----pdxplot2, fig.cap="Tumor growth curves for a batch of control and treated PDXs. Here, the volume is normalized and plots are truncated at 40 days", out.width='4in', fig.wide=TRUE----
plotPDX(brca, batch = "X-4567.BKM120", vol.normal = TRUE, control.col = "#a6611a",
treatment.col = "#018571", major.line.size = 1, max.time = 40)
## ----pdxplot3, fig.cap="Tumor growth curves for a batch of control and treated PDXs generated using patient ID and drug name", out.width='4in', fig.wide=TRUE----
plotPDX(brca, patient.id="X-3078", drug="paclitaxel",control.name = "untreated")
## ----repplot1, fig.cap="Tumor growth curves for a batch of control and treated PDXs with replicates", out.width='4in', fig.wide=TRUE----
data("repdx")
plotPDX(repdx, vol.normal = TRUE, batch = "P1")
## ----repplot2, fig.cap="Errorbar visualization for tumor growth curves of a PDX batch", out.width='4in', fig.wide=TRUE----
plotPDX(repdx, batch = "P3", SE.plot = "errorbar")
## ----repplot3, fig.cap="Ribbon visualization for tumor growth curves of a PDX batch", out.width='4in', fig.wide=TRUE----
plotPDX(repdx, batch = "P4", vol.normal = TRUE, SE.plot = "ribbon")
## ----l4--------------------------------------------------------------------
brca.mr <- summarizeResponse(brca, response.measure = "mRECIST")
brca.mr[1:5, 1:4]
## ----waterFall1, fig.cap="Waterfall plot for binimetinib drug response in PDXs", fig.width=14.1, fig.height=7.8, fig.wide=TRUE----
waterfall(brca, drug="binimetinib", res.measure="best.average.response")
## ----waterFall2, fig.cap="Waterfall plot for BYL719 drug response in PDXs", fig.width=14.1, fig.height=7.8, fig.wide=TRUE----
mut <- summarizeMolecularProfiles(brca,drug = "BYL719", mDataType="mutation")
model.type <- Biobase::exprs(mut)["CDK13", ]
model.type[grepl("Mut", model.type)] <- "mutation"
model.type[model.type!="mutation"] <- "wild type"
model.color <- list("mutation"="#b2182b", "wild type"="#878787")
waterfall(brca, drug="BYL719", res.measure="best.average.response",
model.id=names(model.type), model.type= model.type,
type.color = model.color)
## ----response1-------------------------------------------------------------
data("repdx")
response(repdx, batch="P1", res.measure="angle")
## ----response2-------------------------------------------------------------
data("repdx")
response(repdx, batch="P1", res.measure="lmm")
## ----biomarker1------------------------------------------------------------
data(brca)
drugSensitivitySig(object=brca, drug="tamoxifen", mDataType="RNASeq",
features=c(1,2,3,4,5), sensitivity.measure="slope", fit="lm")
## ----biomarker2------------------------------------------------------------
data(brca)
drugSensitivitySig(object=brca, drug="tamoxifen", mDataType="RNASeq",
features=c(1,2,3,4,5),
sensitivity.measure="best.average.response", fit = "lm")
## ----biomarker3, warning=FALSE---------------------------------------------
data(brca)
drugSensitivitySig(object=brca, drug="tamoxifen", mDataType="RNASeq",
features=c(1,2,3,4,5),
sensitivity.measure="best.average.response", fit="pearson")
## ----x1--------------------------------------------------------------------
model=read.csv(system.file("extdata", "model.csv", package = "Xeva"))
head(model)
## ----x2--------------------------------------------------------------------
drug=read.csv(system.file("extdata", "drug.csv", package = "Xeva"))
head(drug)
## ----x3--------------------------------------------------------------------
experiment=read.csv(system.file("extdata","experiments.csv",package="Xeva"))
head(experiment)
## ----x4--------------------------------------------------------------------
expDesign=readRDS(system.file("extdata","batch_list.rds",package="Xeva"))
expDesign[[1]]
## ----x5--------------------------------------------------------------------
RNASeq=readRDS(system.file("extdata", "rnaseq.rds", package = "Xeva"))
print(RNASeq)
## ----x6--------------------------------------------------------------------
modToBiobaseMap=read.csv(system.file("extdata","modelToExpressionMap.csv",
package = "Xeva"))
head(modToBiobaseMap)
## ----createXevaSet---------------------------------------------------------
xeva.set=createXevaSet(name="example xevaSet", model=model, drug=drug,
experiment=experiment, expDesign=expDesign,
molecularProfiles=list(RNASeq = RNASeq),
modToBiobaseMap = modToBiobaseMap)
print(xeva.set)
## ----sess------------------------------------------------------------------
sessionInfo()
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