Package 'Xeva' reference manual

Title:	Analysis of patient-derived xenograft (PDX) data
Description:	The Xeva package provides efficient and powerful functions for patient-drived xenograft (PDX) based pharmacogenomic data analysis. This package contains a set of functions to perform analysis of patient-derived xenograft data. This package was developed by the BHKLab, for further information please see our documentation.
Authors:	Arvind Mer [aut], Benjamin Haibe-Kains [aut, cre]
Maintainer:	Benjamin Haibe-Kains <[email protected]>
License:	GPL-3
Version:	1.21.0
Built:	2024-06-30 06:01:40 UTC
Source:	https://github.com/bioc/Xeva

area between curves Computes the area between two time-volume curves.

Description

area between curves Computes the area between two time-volume curves.

Usage

ABC(
  contr.time = NULL,
  contr.volume = NULL,
  treat.time = NULL,
  treat.volume = NULL
)
ABC(
  contr.time = NULL,
  contr.volume = NULL,
  treat.time = NULL,
  treat.volume = NULL
)

Arguments

`contr.time`	Time vector for control.
`contr.volume`	Volume vector for control.
`treat.time`	Time vector for treatment.
`treat.volume`	Volume vector for treatment.

Value

Returns batch response object.

Examples

contr.time <- treat.time  <- c(0, 3, 7, 11, 18, 22, 26, 30, 32, 35)
contr.volume<- contr.time * tan(60*pi/180)
treat.volume<- treat.time * tan(15*pi/180)
abc <- ABC(contr.time, contr.volume, treat.time, treat.volume)
par(pty="s")
xylimit <- range(c(contr.time, contr.volume, treat.time, treat.volume))
plot(contr.time, contr.volume, type = "b", xlim = xylimit, ylim = xylimit)
lines(treat.time, treat.volume, type = "b")
polygon(c(treat.time, rev(treat.time)), c(contr.volume, rev(treat.volume)),
        col = "#fa9fb5", border = NA)

contr.time <- treat.time  <- c(0, 3, 7, 11, 18, 22, 26, 30, 32, 35)
contr.volume<- contr.time * tan(60*pi/180)
treat.volume<- treat.time * tan(15*pi/180)
abc <- ABC(contr.time, contr.volume, treat.time, treat.volume)
par(pty="s")
xylimit <- range(c(contr.time, contr.volume, treat.time, treat.volume))
plot(contr.time, contr.volume, type = "b", xlim = xylimit, ylim = xylimit)
lines(treat.time, treat.volume, type = "b")
polygon(c(treat.time, rev(treat.time)), c(contr.volume, rev(treat.volume)),
        col = "#fa9fb5", border = NA)

Add a new experimental design

Description

Add a new experimental design in the expDesign slot.

Usage

addExperimentalDesign(
  object,
  treatment = NULL,
  control = NULL,
  batch.id = NULL,
  replace = FALSE
)

## S4 method for signature 'XevaSet'
addExperimentalDesign(
  object,
  treatment = NULL,
  control = NULL,
  batch.id = NULL,
  replace = FALSE
)
addExperimentalDesign(
  object,
  treatment = NULL,
  control = NULL,
  batch.id = NULL,
  replace = FALSE
)

## S4 method for signature 'XevaSet'
addExperimentalDesign(
  object,
  treatment = NULL,
  control = NULL,
  batch.id = NULL,
  replace = FALSE
)

Arguments

`object`	The `Xeva` dataset.
`treatment`	The `model.id` of treatment.
`control`	The `model.id` of control.
`batch.id`	The `batch.id` for a new batch.
`replace`	If `TRUE`, replace an old batch with new values.

Value

Returns Xeva dataset with new experimental design added.

Examples

data(brca)
brca <- addExperimentalDesign(object=brca, treatment=c("X.6047.LL71"),
        control=c("X.6047.uned"), batch.id="new.batch", replace=FALSE)

data(brca)
brca <- addExperimentalDesign(object=brca, treatment=c("X.6047.LL71"),
        control=c("X.6047.uned"), batch.id="new.batch", replace=FALSE)

compute angle Computes the angle between two time-volume curves.

Description

compute angle Computes the angle between two time-volume curves.

Usage

angle(
  contr.time = NULL,
  contr.volume = NULL,
  treat.time = NULL,
  treat.volume = NULL,
  degree = TRUE
)
angle(
  contr.time = NULL,
  contr.volume = NULL,
  treat.time = NULL,
  treat.volume = NULL,
  degree = TRUE
)

Arguments

`contr.time`	Time vector for control.
`contr.volume`	Volume vector for control.
`treat.time`	Time vector for treatment.
`treat.volume`	Volume vector for treatment.
`degree`	Default `TRUE` will give angle in degrees and `FALSE` will return in radians.

Value

Returns batch response object.

Examples

contr.time <- treat.time  <- c(0, 3, 7, 11, 18, 22, 26, 30, 32, 35)
contr.volume<- contr.time * tan(60*pi/180)
treat.volume<- treat.time * tan(15*pi/180)
ang <- angle(contr.time, contr.volume, treat.time, treat.volume)
print(ang)
par(pty="s")
xylimit <- range(c(contr.time, contr.volume, treat.time, treat.volume))
plot(contr.time, contr.volume, type = "b", xlim = xylimit, ylim = xylimit)
lines(treat.time, treat.volume, type = "b")
abline(lm(contr.volume~contr.time))
abline(lm(treat.volume~treat.time))
contr.time <- treat.time  <- c(0, 3, 7, 11, 18, 22, 26, 30, 32, 35)
contr.volume<- contr.time * tan(60*pi/180)
treat.volume<- treat.time * tan(15*pi/180)
ang <- angle(contr.time, contr.volume, treat.time, treat.volume)
print(ang)
par(pty="s")
xylimit <- range(c(contr.time, contr.volume, treat.time, treat.volume))
plot(contr.time, contr.volume, type = "b", xlim = xylimit, ylim = xylimit)
lines(treat.time, treat.volume, type = "b")
abline(lm(contr.volume~contr.time))
abline(lm(treat.volume~treat.time))

area under the curve `AUC` Returns area under the curve

Description

area under the curve AUC Returns area under the curve

Usage

AUC(time, volume)
AUC(time, volume)

Arguments

`time`	A `vector` of time points recorded for the experiment.
`volume`	First `vector` of volume.

Value

Returns angle and slope object.

Examples

time  <- c(0, 3, 7, 11, 18, 22, 26, 30, 32, 35)
volume1<- time * tan(30*pi/180)
volume2<- time * tan(45*pi/180)
auc1 <- AUC(time, volume1)
auc2 <- AUC(time, volume2)
par(pty="s")
xylimit <- range(c(time, volume1, volume2))
plot(time, volume1, type = "b", xlim = xylimit, ylim = xylimit)
lines(time, volume2, type = "b")
abline(lm(volume1~time))
abline(lm(volume2~time))
time  <- c(0, 3, 7, 11, 18, 22, 26, 30, 32, 35)
volume1<- time * tan(30*pi/180)
volume2<- time * tan(45*pi/180)
auc1 <- AUC(time, volume1)
auc2 <- AUC(time, volume2)
par(pty="s")
xylimit <- range(c(time, volume1, volume2))
plot(time, volume1, type = "b", xlim = xylimit, ylim = xylimit)
lines(time, volume2, type = "b")
abline(lm(volume1~time))
abline(lm(volume2~time))

Get batch information

Description

Get batch information from a Xeva dataset.

Usage

batchInfo(
  object,
  batch = NULL,
  model.id = NULL,
  model.id.type = c("any", "control", "treatment")
)

## S4 method for signature 'XevaSet'
batchInfo(
  object,
  batch = NULL,
  model.id = NULL,
  model.id.type = c("any", "control", "treatment")
)
batchInfo(
  object,
  batch = NULL,
  model.id = NULL,
  model.id.type = c("any", "control", "treatment")
)

## S4 method for signature 'XevaSet'
batchInfo(
  object,
  batch = NULL,
  model.id = NULL,
  model.id.type = c("any", "control", "treatment")
)

Arguments

`object`	The Xeva object from which batch information is obtained.
`batch`	Name of the batch. Default `NULL`.
`model.id`	Model ID for which need to be searched in the batches. Default `NULL`.
`model.id.type`	Type of the model ID in a batch. See the Details section below.

Details

By default this function will return the names of all the batches present in the dataset. If a batch specified, it will return the experiment design (control and treatment model IDs) of that particular batch. If model.id is specified, it will return the names of all the batches where this particuler model.id is present. If both batch and model.id are specified, batch will take precedent.

For model.id.type, the default value 'any' will return all the batch IDs where the given model ID is present in any arm (ie. control or treatment) of the batch. It can also be restricted to look only for treatment (or control) arm by specifying the type.

Value

A Vector with batch names.

Examples

data(brca)
##to get all the batch names
batch.name <- batchInfo(brca)

##to get a specific batch
batch.design <- batchInfo(brca, batch=batch.name[1])

##to get all the batches where a model.id is present
batchInfo(brca, model.id="X.6047.uned")

data(brca)
##to get all the batch names
batch.name <- batchInfo(brca)

##to get a specific batch
batch.design <- batchInfo(brca, batch=batch.name[1])

##to get all the batches where a model.id is present
batchInfo(brca, model.id="X.6047.uned")

PDXE breast cancer dataset

Description

A Xeva object containing only breast cancer PDXs from the PDXE dataset For details about PDX-MI, see: Gao et al. High-throughput screening using patient-derived tumor xenografts to predict clinical trial drug response. Nature medicine, 21(11):1318, 2015.

Usage

data(brca)
data(brca)

Format

An object of class XevaSet of length 1.

Source

https://www.nature.com/articles/nm.3954?draft=journal

XevaSet constructor

Description

A constructor to create XevaSet. Only objects returned by this constructor are expected to work with the XevaSet methods.

Usage

createXevaSet(
  name,
  model = data.frame(),
  drug = data.frame(),
  experiment = data.frame(),
  expDesign = list(),
  modelSensitivity = data.frame(),
  batchSensitivity = data.frame(),
  molecularProfiles = list(),
  modToBiobaseMap = data.frame()
)
createXevaSet(
  name,
  model = data.frame(),
  drug = data.frame(),
  experiment = data.frame(),
  expDesign = list(),
  modelSensitivity = data.frame(),
  batchSensitivity = data.frame(),
  molecularProfiles = list(),
  modToBiobaseMap = data.frame()
)

Arguments

`name`	A `character` string detailing the name of the dataset.
`model`	A `data.frame` containing the annotations for all the models used in the experiment.
`drug`	A `data.frame` containing the annotations for all the drugs profiled in the dataset, across all data types.
`experiment`	A `data.frame` containing all experiment information.
`expDesign`	A list containing name of the batch, control and treatment model.id
`modelSensitivity`	A `data.frame` containing sensitivity for each model
`batchSensitivity`	A `data.frame` containing sensitivity for each batch
`molecularProfiles`	A `list` of `ExpressionSet` objects containing different molecular profiles.
`modToBiobaseMap`	A `data.frame` containing model.id corresponding Biobase object id and name of the molecularProfiles

Details

This function creates a XevaSet object. It takes different model infromation and genomic data as input. For detailed discription of all varaibles please see Xeva vignette section "Creating new Xeva object"

Value

Returns Xeva object

Examples

## read raw data files containg PDX experiment information and genomic data
model = read.csv(system.file("extdata", "model.csv", package = "Xeva"))
drug = read.csv(system.file("extdata", "drug.csv", package = "Xeva"))
experiment= read.csv(system.file("extdata", "experiments.csv", package = "Xeva"))
expDesign=readRDS(system.file("extdata", "batch_list.rds", package = "Xeva"))
RNASeq=readRDS(system.file("extdata", "rnaseq.rds", package = "Xeva"))
modToBiobaseMap=read.csv(system.file("extdata", "modelToExpressionMap.csv", package = "Xeva"))

## create Xeva object
xeva.set = createXevaSet(name="example xevaSet", model=model, drug=drug,
                         experiment=experiment, expDesign=expDesign,
                         molecularProfiles=list(RNASeq = RNASeq),
                         modToBiobaseMap = modToBiobaseMap)
print(xeva.set)

## read raw data files containg PDX experiment information and genomic data
model = read.csv(system.file("extdata", "model.csv", package = "Xeva"))
drug = read.csv(system.file("extdata", "drug.csv", package = "Xeva"))
experiment= read.csv(system.file("extdata", "experiments.csv", package = "Xeva"))
expDesign=readRDS(system.file("extdata", "batch_list.rds", package = "Xeva"))
RNASeq=readRDS(system.file("extdata", "rnaseq.rds", package = "Xeva"))
modToBiobaseMap=read.csv(system.file("extdata", "modelToExpressionMap.csv", package = "Xeva"))

## create Xeva object
xeva.set = createXevaSet(name="example xevaSet", model=model, drug=drug,
                         experiment=experiment, expDesign=expDesign,
                         molecularProfiles=list(RNASeq = RNASeq),
                         modToBiobaseMap = modToBiobaseMap)
print(xeva.set)

plot dose data

Description

plot data for dose in model.id

Usage

dosePlot(
  object,
  model.id,
  max.time = NULL,
  treatment.only = FALSE,
  vol.normal = FALSE,
  concurrent.time = FALSE,
  point.shape = 21,
  point.size = 3,
  line.size = 4,
  point.color = "#878787",
  line.color = "#bababa",
  fill.col = c("#f5f5f5", "#E55100"),
  modify.x.axis = FALSE
)
dosePlot(
  object,
  model.id,
  max.time = NULL,
  treatment.only = FALSE,
  vol.normal = FALSE,
  concurrent.time = FALSE,
  point.shape = 21,
  point.size = 3,
  line.size = 4,
  point.color = "#878787",
  line.color = "#bababa",
  fill.col = c("#f5f5f5", "#E55100"),
  modify.x.axis = FALSE
)

Arguments

`object`	Xeva object.
`model.id`	one or multiple model.id
`max.time`	Maximum time point of the plot. Default `NULL` will plot complete data
`treatment.only`	Default `FALSE`. Given full data `treatment.only=TRUE` will plot data only during treatment
`vol.normal`	Default `FALSE`. If `TRUE`, volume will be normalized
`concurrent.time`	Default `FALSE`. If `TRUE`, cut the batch data such that control and treatment will end at the same time point
`point.shape`	shape of the point
`point.size`	size of the point
`line.size`	size of the line
`point.color`	color for point
`line.color`	color for line
`fill.col`	a vector with color to fill
`modify.x.axis`	Default `FALSE`

Value

A ggplot2 plot

Examples

data(brca)
dosePlot(brca, model.id=c("X.6047.LJ16","X.6047.LJ16.trab"), fill.col=c("#f5f5f5", "#993404"))
data(brca)
dosePlot(brca, model.id=c("X.6047.LJ16","X.6047.LJ16.trab"), fill.col=c("#f5f5f5", "#993404"))

Download a XevaSet object or table of available XevaSet objects

Description

This function allows you to see the available XevaSet object and download them for use with this package. The XevaSet have been extensively curated and organised within a XevaSet class, enabling use with all the analysis tools provided in Xeva.

Usage

downloadXevaSet(
  name = NULL,
  saveDir = file.path(".", "XevaSet"),
  XevaSetFileName = NULL,
  verbose = TRUE
)
downloadXevaSet(
  name = NULL,
  saveDir = file.path(".", "XevaSet"),
  XevaSetFileName = NULL,
  verbose = TRUE
)

Arguments

`name`	Character string, the name of the XevaSet to download.
`saveDir`	`Character` string with the folder path where the XevaSet should be saved. Defaults to './XevaSet/'. Will create directory if it does not exist.
`XevaSetFileName`	`character` string, the file name to save the dataset under
`verbose`	`bool` Should status messages be printed during download. Defaults to TRUE.

Value

A data.frame if name is NULL, showing all the available XevaSet objects. If name is specified, it will download the dataset from our server

Examples

downloadXevaSet()
##to download a dataset
#library(Xeva)
#PDXE_BRCA = downloadXevaSet(name="PDXE_BRCA", saveDir="XevaSet")

downloadXevaSet()
##to download a dataset
#library(Xeva)
#PDXE_BRCA = downloadXevaSet(name="PDXE_BRCA", saveDir="XevaSet")

Get drug information Get the drug information slot from a XevaSet object.

Description

Get drug information Get the drug information slot from a XevaSet object.

Usage

drugInform(object)

## S4 method for signature 'XevaSet'
drugInform(object)
drugInform(object)

## S4 method for signature 'XevaSet'
drugInform(object)

Arguments

object

The XevaSet to retrieve drug information from.

Value

A data.frame with the drug annotations.

Examples

data(brca)
head(drugInform(brca))
data(brca)
head(drugInform(brca))

get drug sensitivity values

Description

Given a Xeva object and drug name, this function will return sensitivity values for all the genes/features.

Usage

drugSensitivitySig(
  object,
  drug,
  mDataType = NULL,
  molData = NULL,
  features = NULL,
  model.ids = NULL,
  model2bidMap = NULL,
  sensitivity.measure = "slope",
  fit = c("lm", "CI", "pearson", "spearman", NA),
  standardize = c("SD", "rescale", "none"),
  nthread = 1,
  tissue = NULL,
  verbose = TRUE
)
drugSensitivitySig(
  object,
  drug,
  mDataType = NULL,
  molData = NULL,
  features = NULL,
  model.ids = NULL,
  model2bidMap = NULL,
  sensitivity.measure = "slope",
  fit = c("lm", "CI", "pearson", "spearman", NA),
  standardize = c("SD", "rescale", "none"),
  nthread = 1,
  tissue = NULL,
  verbose = TRUE
)

Arguments

`object`	The `Xeva` dataset.
`drug`	Name of the drug.
`mDataType`	Molecular data type.
`molData`	External data matrix. Rows as features and columns as samples.
`features`	Set which molecular data features to use. Default `NULL` will use all features.
`model.ids`	Set which `model.id` to use from the dataset. Default `NULL` will use all `model.id`s.
`model2bidMap`	A `data.frame` with `model.id` and `biobase.id`. Default `NULL` will use internal mapping.
`sensitivity.measure`	Name of the sensitivity measure.
`fit`	Association method to use, can be 'lm', 'CI', 'pearson' or 'spearman'. If 'NA' only the data will be return. Default `lm`.
`standardize`	Default `SD`. Name of the method to use for data standardization before fitting.
`nthread`	number of threads
`tissue`	tissue type. Default `NULL` uses `'tissue'` from `object`.
`verbose`	Default `TRUE` will show information

Details

Method to compute association can be specified by fit. It can be one of the:

"lm" for linear models
"CI" for concordance index
"pearson" for Pearson correlation
"spearman" for Spearman correlation

If fit is set to NA, processed data (an ExpressionSet) will be returned.

A matrix of values can be directly passed to molData. In case where a model.id maps to multiple biobase.ids, the first biobase.id in the data.frame will be used.

Value

A data.frame with features and values.

Examples

data(brca)
senSig <- drugSensitivitySig(object=brca, drug="tamoxifen",
                             mDataType="RNASeq", features=c(1,2,3,4,5),
                             sensitivity.measure="slope", fit = "lm")

## example to compute the Pearson correlation between gene expression and PDX response
senSig <- drugSensitivitySig(object=brca, drug="tamoxifen",
                             mDataType="RNASeq", features=c(1,2,3,4,5),
                             sensitivity.measure="slope", fit = "pearson")

data(brca)
senSig <- drugSensitivitySig(object=brca, drug="tamoxifen",
                             mDataType="RNASeq", features=c(1,2,3,4,5),
                             sensitivity.measure="slope", fit = "lm")

## example to compute the Pearson correlation between gene expression and PDX response
senSig <- drugSensitivitySig(object=brca, drug="tamoxifen",
                             mDataType="RNASeq", features=c(1,2,3,4,5),
                             sensitivity.measure="slope", fit = "pearson")

Get PDX experiment data

Description

For a given model.id, getExperiment will

Usage

getExperiment(
  object,
  model.id = NULL,
  batch = NULL,
  patient.id = NULL,
  drug = NULL,
  control.name = NULL,
  treatment.only = FALSE,
  max.time = NULL,
  vol.normal = FALSE,
  log.volume = FALSE,
  return.list = FALSE,
  impute.value = FALSE,
  concurrent.time = FALSE
)

## S4 method for signature 'XevaSet'
getExperiment(
  object,
  model.id = NULL,
  batch = NULL,
  patient.id = NULL,
  drug = NULL,
  control.name = NULL,
  treatment.only = FALSE,
  max.time = NULL,
  vol.normal = FALSE,
  log.volume = FALSE,
  return.list = FALSE,
  impute.value = FALSE,
  concurrent.time = FALSE
)
getExperiment(
  object,
  model.id = NULL,
  batch = NULL,
  patient.id = NULL,
  drug = NULL,
  control.name = NULL,
  treatment.only = FALSE,
  max.time = NULL,
  vol.normal = FALSE,
  log.volume = FALSE,
  return.list = FALSE,
  impute.value = FALSE,
  concurrent.time = FALSE
)

## S4 method for signature 'XevaSet'
getExperiment(
  object,
  model.id = NULL,
  batch = NULL,
  patient.id = NULL,
  drug = NULL,
  control.name = NULL,
  treatment.only = FALSE,
  max.time = NULL,
  vol.normal = FALSE,
  log.volume = FALSE,
  return.list = FALSE,
  impute.value = FALSE,
  concurrent.time = FALSE
)

Arguments

`object`	The `XevaSet` object.
`model.id`	The `model.id` for which data is required, multiple IDs are allowed.
`batch`	Batch name from the `XevaSet` or experiment design.
`patient.id`	Patient id from the `XevaSet`. Default `NULL`.
`drug`	Name of the drug.
`control.name`	Name of drug used as control. Default `NULL`.
`treatment.only`	Default `FALSE`. If `TRUE`, give data for non-zero dose periods only (if dose data are available).
`max.time`	Maximum time for data.
`vol.normal`	If TRUE it will normalize the volume. Default `FALSE`.
`log.volume`	If TRUE log of the volume will be used. Default `FALSE`.
`return.list`	Default `FALSE` will return a `data.frame`.
`impute.value`	Default `FALSE`. If `TRUE`, impute the missing values.
`concurrent.time`	Default `FALSE`. If `TRUE`, cut the batch data such that control and treatment will end at same time point.

Value

a data.fram will all the the values stored in experiment slot

Examples

data(brca)

getExperiment(brca, model.id="X.6047.uned", treatment.only=TRUE)

getExperiment(brca, model.id=c("X.6047.uned", "X.6047.pael"), treatment.only=TRUE)

getExperiment(brca, batch="X-6047.paclitaxel", treatment.only=TRUE)

ed <- list(batch.name="myBatch", treatment=c("X.6047.LJ16","X.6047.LJ16.trab"),
             control=c("X.6047.uned"))

getExperiment(brca, batch=ed)

data(brca)

getExperiment(brca, model.id="X.6047.uned", treatment.only=TRUE)

getExperiment(brca, model.id=c("X.6047.uned", "X.6047.pael"), treatment.only=TRUE)

getExperiment(brca, batch="X-6047.paclitaxel", treatment.only=TRUE)

ed <- list(batch.name="myBatch", treatment=c("X.6047.LJ16","X.6047.LJ16.trab"),
             control=c("X.6047.uned"))

getExperiment(brca, batch=ed)

Get molecular profiles from a XevaSet object

Description

This function serves to get molecular profiles from a XevaSet object.

Usage

getMolecularProfiles(object, data.type)
getMolecularProfiles(object, data.type)

Arguments

`object`	The `XevaSet`.
`data.type`	`character`, where one of the molecular data types is needed.

Value

An ExpressionSet where sample names are the biobase.id of the model.

Examples

data(brca)
brca.RNA <- getMolecularProfiles(brca, data.type="RNASeq")
data(brca)
brca.RNA <- getMolecularProfiles(brca, data.type="RNASeq")

linear mixed model

Description

Comput the linear mixed model (lmm) statistics for a PDX batch

Usage

lmm(data)
lmm(data)

Arguments

data

a data.frame containg a batch data

Details

The input data.frame (data) must contain these columns: model.id, volume, time, exp.type

Value

Returns a fit object

Examples

data(repdx)
data <- getExperiment(repdx, batch = "P1")$model
lmm(data)

data(repdx)
data <- getExperiment(repdx, batch = "P1")$model
lmm(data)

modelInfo Generic Generic for modelInfo method

Description

modelInfo Generic Generic for modelInfo method

Usage

modelInfo(object, mDataType = NULL)

## S4 method for signature 'XevaSet'
modelInfo(object, mDataType = NULL)
modelInfo(object, mDataType = NULL)

## S4 method for signature 'XevaSet'
modelInfo(object, mDataType = NULL)

Arguments

`object`	Xeva object
`mDataType`	Molecular data type.

Value

A data.frame with the model annotations.

Examples

data(brca)
mid <- modelInfo(brca)
head(mid)

data(brca)
mid <- modelInfo(brca)
head(mid)

Computes the mRECIST

Description

mRECIST Returns the mRECIST for given volume response.

Usage

mRECIST(time, volume, min.time = 10, return.detail = FALSE)
mRECIST(time, volume, min.time = 10, return.detail = FALSE)

Arguments

`time`	Value of best response.
`volume`	Value of best average response.
`min.time`	Minimum time after which tumor volume will be considered.
`return.detail`	Default `FALSE`. If `TRUE`, return all intermediate values.

Value

Returns the mRECIST.

Examples

time  <- c(0, 3, 7, 11, 18, 22, 26, 30, 32, 35)
volume<- c(250.8, 320.4, 402.3, 382.6, 384, 445.9, 460.2, 546.8, 554.3, 617.9)
mRECIST(time, volume, min.time=10, return.detail=FALSE)
time  <- c(0, 3, 7, 11, 18, 22, 26, 30, 32, 35)
volume<- c(250.8, 320.4, 402.3, 382.6, 384, 445.9, 460.2, 546.8, 554.3, 617.9)
mRECIST(time, volume, min.time=10, return.detail=FALSE)

PDX-MI data

Description

A dataset containing PDX models minimal information (PDX-MI) standard and corresponding Xeva variable.

Usage

data(PDXMI)
data(PDXMI)

Format

An object of class data.frame with 45 rows and 4 columns.

Details

For details about PDX-MI, see:

Meehan, Terrence F., et al. "PDX-MI: minimal information for patient-derived tumor xenograft models." Cancer research 77.21 (2017): e62-e66.

Source

http://cancerres.aacrjournals.org/lookup/doi/10.1158/0008-5472.CAN-17-0582

To plot mRECIST values

Description

plotmRECIST plots the mRECIST matrix obtained from summarizeResponse.

Usage

plotmRECIST(
  mat,
  control.name = NA,
  control.col = "#238b45",
  drug.col = "black",
  colPalette = NULL,
  name = "Drug & Models",
  sort = TRUE,
  row_fontsize = 12,
  col_fontsize = 12,
  draw_plot = TRUE
)
plotmRECIST(
  mat,
  control.name = NA,
  control.col = "#238b45",
  drug.col = "black",
  colPalette = NULL,
  name = "Drug & Models",
  sort = TRUE,
  row_fontsize = 12,
  col_fontsize = 12,
  draw_plot = TRUE
)

Arguments

`mat`	The mRECIST matrix where rows are drugs and columns are patients.
`control.name`	Name of the control.
`control.col`	Color of the control.
`drug.col`	Color of the drug names.
`colPalette`	Color palette for mRECIST values.
`name`	Title of the plot.
`sort`	If matrix should be sorted before plotting.
`row_fontsize`	Size of the row name font.
`col_fontsize`	Size of the column name font.
`draw_plot`	Default `TRUE` will plot the figure. If `FALSE`, return an object.

Value

mRECIST plot.

Examples

data(brca)
brca.mr <- summarizeResponse(brca, response.measure = "mRECIST", group.by="patient.id")
plotmRECIST(as.matrix(brca.mr), control.name = "untreated")
data(brca)
brca.mr <- summarizeResponse(brca, response.measure = "mRECIST", group.by="patient.id")
plotmRECIST(as.matrix(brca.mr), control.name = "untreated")

Plot batch data

Description

Plot data for a batch.id, experiment design or model.id

Usage

plotPDX(
  object,
  batch = NULL,
  patient.id = NULL,
  drug = NULL,
  model.id = NULL,
  model.color = NULL,
  control.name = NULL,
  max.time = NULL,
  treatment.only = FALSE,
  vol.normal = FALSE,
  impute.value = TRUE,
  concurrent.time = FALSE,
  control.col = "#e41a1c",
  treatment.col = "#377eb8",
  title = "",
  xlab = "Time",
  ylab = "Volume",
  log.y = FALSE,
  SE.plot = c("all", "none", "errorbar", "ribbon"),
  aspect.ratio = c(1, NULL),
  minor.line.size = 0.5,
  major.line.size = 0.7
)

plotBatch(
  object,
  batch = NULL,
  patient.id = NULL,
  drug = NULL,
  control.name = NULL,
  max.time = NULL,
  treatment.only = FALSE,
  vol.normal = FALSE,
  impute.value = TRUE,
  concurrent.time = FALSE,
  control.col = "#6baed6",
  treatment.col = "#fc8d59",
  title = "",
  xlab = "Time",
  ylab = "Volume",
  log.y = FALSE,
  SE.plot = c("all", "none", "errorbar", "ribbon"),
  aspect.ratio = c(1, NULL),
  minor.line.size = 0.5,
  major.line.size = 0.7
)
plotPDX(
  object,
  batch = NULL,
  patient.id = NULL,
  drug = NULL,
  model.id = NULL,
  model.color = NULL,
  control.name = NULL,
  max.time = NULL,
  treatment.only = FALSE,
  vol.normal = FALSE,
  impute.value = TRUE,
  concurrent.time = FALSE,
  control.col = "#e41a1c",
  treatment.col = "#377eb8",
  title = "",
  xlab = "Time",
  ylab = "Volume",
  log.y = FALSE,
  SE.plot = c("all", "none", "errorbar", "ribbon"),
  aspect.ratio = c(1, NULL),
  minor.line.size = 0.5,
  major.line.size = 0.7
)

plotBatch(
  object,
  batch = NULL,
  patient.id = NULL,
  drug = NULL,
  control.name = NULL,
  max.time = NULL,
  treatment.only = FALSE,
  vol.normal = FALSE,
  impute.value = TRUE,
  concurrent.time = FALSE,
  control.col = "#6baed6",
  treatment.col = "#fc8d59",
  title = "",
  xlab = "Time",
  ylab = "Volume",
  log.y = FALSE,
  SE.plot = c("all", "none", "errorbar", "ribbon"),
  aspect.ratio = c(1, NULL),
  minor.line.size = 0.5,
  major.line.size = 0.7
)

Arguments

`object`	Xeva object.
`batch`	Batch name or experiment design list.
`patient.id`	Patient id from the `XevaSet`. Default `NULL`.
`drug`	Name of the drug. Default `NULL`.
`model.id`	One or multiple model.id. Default `NULL`.
`model.color`	Color for `model.id`. Default `NULL`.
`control.name`	Name of the control sample.
`max.time`	Maximum time point of the plot. Default `NULL` will plot complete data.
`treatment.only`	Default `FALSE`. Given full data `treatment.only=TRUE` will plot data only during treatment.
`vol.normal`	Default `FALSE`. If `TRUE`, volume will be normalized.
`impute.value`	Default `TRUE` will impute values if missing.
`concurrent.time`	Default `FALSE`. If `TRUE`, cut the batch data such that control and treatment will end at the same time point.
`control.col`	Color for control plots.
`treatment.col`	Color for treatment plots.
`title`	Title of the plot.
`xlab`	Title of the x-axis.
`ylab`	Title of the y-axis.
`log.y`	Default `FALSE`. If `TRUE`, y-axis will be log-transformed.
`SE.plot`	Plot type. Default `"all"` will plot all plots and average curves. Possible values are `"all"`, `"none"`, `"errorbar"`, and `"ribbon"`.
`aspect.ratio`	Default `1` will create a plot of equal width and height.
`minor.line.size`	Line size for minor lines. Default `0.5`.
`major.line.size`	Line size for major lines. Default `0.7`.

Value

A ggplot2 plot with control and treatment batch data.

Examples

data(brca)
plotPDX(brca, model.id=c("X.6047.LJ16","X.6047.LJ16.trab"))

plotPDX(brca, batch="X-1004.BGJ398", vol.normal=TRUE)
expDesign <- list(batch.name="myBatch", treatment=c("X.6047.LJ16","X.6047.LJ16.trab"),
             control=c("X.6047.uned"))
plotBatch(brca, batch=expDesign, vol.normal=TRUE)
plotBatch(brca, batch=expDesign, vol.normal=FALSE, SE.plot = "errorbar")
data(brca)
plotPDX(brca, model.id=c("X.6047.LJ16","X.6047.LJ16.trab"))

plotPDX(brca, batch="X-1004.BGJ398", vol.normal=TRUE)
expDesign <- list(batch.name="myBatch", treatment=c("X.6047.LJ16","X.6047.LJ16.trab"),
             control=c("X.6047.uned"))
plotBatch(brca, batch=expDesign, vol.normal=TRUE)
plotBatch(brca, batch=expDesign, vol.normal=FALSE, SE.plot = "errorbar")

Print the batch response

Description

Print the batch response

Usage

## S3 method for class 'batchResponse'
print(x, ...)
## S3 method for class 'batchResponse'
print(x, ...)

Arguments

`x`	batchResponse object
`...`	Other arguments

Value

prints the batchResponse

Print the model response

Description

Print the model response

Usage

## S3 method for class 'modelResponse'
print(x, ...)
## S3 method for class 'modelResponse'
print(x, ...)

Arguments

`x`	modelResponse object
`...`	Other arguments

Value

prints the modelResponse

Print the pdx batch

Description

Print the pdx batch

Usage

## S3 method for class 'pdxBatch'
print(x, ...)
## S3 method for class 'pdxBatch'
print(x, ...)

Arguments

`x`	pdxBatch object
`...`	Other arguments

Value

prints pdxBatch

Example PDX dataset

Description

A Xeva object containing anonymous PDX data with replicates. Each batch has 5 replicates.

Usage

data(repdx)
data(repdx)

Format

An object of class XevaSet of length 1.

compute PDX response

Description

response Computes the drug response of an individual PDX model or batch.

Usage

response(
  object,
  model.id = NULL,
  batch = NULL,
  res.measure = c("mRECIST", "slope", "AUC", "angle", "abc", "TGI", "lmm"),
  treatment.only = FALSE,
  max.time = NULL,
  impute.value = TRUE,
  min.time = 10,
  concurrent.time = TRUE,
  vol.normal = FALSE,
  log.volume = FALSE,
  verbose = TRUE
)
response(
  object,
  model.id = NULL,
  batch = NULL,
  res.measure = c("mRECIST", "slope", "AUC", "angle", "abc", "TGI", "lmm"),
  treatment.only = FALSE,
  max.time = NULL,
  impute.value = TRUE,
  min.time = 10,
  concurrent.time = TRUE,
  vol.normal = FALSE,
  log.volume = FALSE,
  verbose = TRUE
)

Arguments

`object`	Xeva object.
`model.id`	`model.id` for which the durg response is to be computed.
`batch`	`batch.id` or experiment design for which the drug response is to be computed.
`res.measure`	Drug response measure. See `Details` below
`treatment.only`	Default `FALSE`. If `TRUE`, give data for non-zero dose periods only (if dose data are available).
`max.time`	Maximum time for data.
`impute.value`	Default `FALSE`. If `TRUE`, impute the missing values.
`min.time`	Default 10 days. Used for mRECIST computation.
`concurrent.time`	Default `FALSE`. If `TRUE`, cut the batch data such that control and treatment will end at same time point.
`vol.normal`	If TRUE it will normalize the volume. Default `FALSE`.
`log.volume`	If TRUE log of the volume will be used for response calculation. Default `FALSE`
`verbose`	Default `TRUE` will print information.

Details

At present the following response measures are implemented

mRECIST Computes mRECIST for individual PDX models
slope Computes slope of the fitted individual PDX curves
AUC Computes area under a PDX curve for individual PDX models
angle Computes angle between treatment and control PDX curves
abc Computes area between the treatment and control PDX curves
TGI Computes tumor growth inhibition using treatment and control PDX curves
lmm Computes linear mixed model (lmm) statistics for a PDX batch

Value

Returns model or batch drug response object.

Examples

data(brca)
response(brca, model.id="X.1004.BG98", res.measure="mRECIST")

response(brca, batch="X-6047.paclitaxel", res.measure="angle")

ed <- list(batch.name="myBatch", treatment=c("X.6047.LJ16","X.6047.LJ16.trab"),
             control=c("X.6047.uned"))
response(brca, batch=ed, res.measure="angle")

data(brca)
response(brca, model.id="X.1004.BG98", res.measure="mRECIST")

response(brca, batch="X-6047.paclitaxel", res.measure="angle")

ed <- list(batch.name="myBatch", treatment=c("X.6047.LJ16","X.6047.LJ16.trab"),
             control=c("X.6047.uned"))
response(brca, batch=ed, res.measure="angle")

To select model IDs based on drug name and/or tissue type.

Description

To select model IDs based on drug name and/or tissue type.

Usage

selectModelIds(object, drug = NULL, drug.match.exact = TRUE, tissue = NULL)

## S4 method for signature 'XevaSet'
selectModelIds(object, drug = NULL, drug.match.exact = TRUE, tissue = NULL)
selectModelIds(object, drug = NULL, drug.match.exact = TRUE, tissue = NULL)

## S4 method for signature 'XevaSet'
selectModelIds(object, drug = NULL, drug.match.exact = TRUE, tissue = NULL)

Arguments

`object`	The `XevaSet`.
`drug`	Name of the `drug`.
`drug.match.exact`	Default `TRUE`.
`tissue`	Tumor type. Default `NULL`.

Value

A vector with the matched model.ids.

Examples

data(brca)
df = selectModelIds(brca, drug="trastuzumab", drug.match.exact=TRUE, tissue="BRCA")
head(df)
df2 = selectModelIds(brca, drug="trastuzumab", drug.match.exact=FALSE)
head(df2)

data(brca)
df = selectModelIds(brca, drug="trastuzumab", drug.match.exact=TRUE, tissue="BRCA")
head(df)
df2 = selectModelIds(brca, drug="trastuzumab", drug.match.exact=FALSE)
head(df2)

Get sensitivity for an Xeva object

Description

Given a Xeva object, it will return a data.frame detailing sensitivity information.

Usage

sensitivity(object, type = c("model", "batch"), sensitivity.measure = NULL)
sensitivity(object, type = c("model", "batch"), sensitivity.measure = NULL)

Arguments

`object`	The `Xeva` dataset.
`type`	Sensitivity type (either model or batch).
`sensitivity.measure`	Name of the `sensitivity.measure`. Default `NULL` will return all sensitivity measures.

Value

A data.frame with model or batch ID and sensitivity values.

Examples

data(brca)
head(sensitivity(brca, type="batch"))
head(sensitivity(brca, type="model"))
data(brca)
head(sensitivity(brca, type="batch"))
head(sensitivity(brca, type="model"))

set PDX response

Description

setResponse sets response of all PDXs in an Xeva object.

Usage

setResponse(
  object,
  res.measure = c("mRECIST", "slope", "AUC", "angle", "abc", "TGI", "lmm"),
  min.time = 10,
  treatment.only = FALSE,
  max.time = NULL,
  vol.normal = FALSE,
  impute.value = TRUE,
  concurrent.time = TRUE,
  log.volume = FALSE,
  verbose = TRUE
)
setResponse(
  object,
  res.measure = c("mRECIST", "slope", "AUC", "angle", "abc", "TGI", "lmm"),
  min.time = 10,
  treatment.only = FALSE,
  max.time = NULL,
  vol.normal = FALSE,
  impute.value = TRUE,
  concurrent.time = TRUE,
  log.volume = FALSE,
  verbose = TRUE
)

Arguments

`object`	Xeva object.
`res.measure`	Response measure, multiple measures are allowed. See `Details` below
`min.time`	Minimum number of days for mRECIST computation. Default 10 days.
`treatment.only`	Default `FALSE`. If `TRUE`, give data for non-zero dose periods only (if dose data are available).
`max.time`	Maximum number of days to consider for analysis. Data byond this will be discarded. Default `NULL` takes full data.
`vol.normal`	If TRUE it will will normalize the volume. Default `FALSE`
`impute.value`	Default `FALSE`. If `TRUE`, impute the missing volume values.
`concurrent.time`	Default `FALSE`. If `TRUE`, cut the batch data such that control and treatment will end at same time point.
`log.volume`	If TRUE log of the volume will be used for response calculation. Default `FALSE`
`verbose`	Default `TRUE` will print information.

Details

At present fellowing response measure are implemented

mRECIST Computes mRECIST for indivial PDX model
slope Computes slope of the fitted indivial PDX curve
AUC Computes area under a PDX curve for indivial PDX model
angle Computes angle between treatment and control PDX curves
abc Computes area between the treatment and control PDX curves
TGI Computes tumor growth inhibition using treatment and control PDX curves
lmm Computes linear mixed model (lmm) statistics for a PDX batch

Value

Returns updated Xeva object.

Examples

data(brca)
brca  <- setResponse(brca, res.measure = c("mRECIST"), verbose=FALSE)
data(brca)
brca  <- setResponse(brca, res.measure = c("mRECIST"), verbose=FALSE)

Computes slope

Description

slope returns the slope for given time and volume data.

Usage

slope(time, volume, degree = TRUE)
slope(time, volume, degree = TRUE)

Arguments

`time`	A `vector` of time.
`volume`	A `vector` of volume.
`degree`	Default `TRUE` will give angle in degrees and `FALSE` will return in radians.

Value

Returns the slope and a fit object.

Examples

time  <- c(0, 3, 7, 11, 18, 22, 26, 30, 32, 35)
volume<- c(250.8, 320.4, 402.3, 382.6, 384, 445.9, 460.2, 546.8, 554.3, 617.9)
sl <- slope(time, volume)
par(pty="s")
xylimit <- range(c(time, volume))
plot(time, volume, type = "b", xlim = xylimit, ylim = xylimit)
abline(lm(volume~time))
time  <- c(0, 3, 7, 11, 18, 22, 26, 30, 32, 35)
volume<- c(250.8, 320.4, 402.3, 382.6, 384, 445.9, 460.2, 546.8, 554.3, 617.9)
sl <- slope(time, volume)
par(pty="s")
xylimit <- range(c(time, volume))
plot(time, volume, type = "b", xlim = xylimit, ylim = xylimit)
abline(lm(volume~time))

Subset Xeva object.

Description

Subset Xeva object.

Usage

subsetXeva(object, ids, id.name, keep.batch = TRUE)
subsetXeva(object, ids, id.name, keep.batch = TRUE)

Arguments

`object`	The `XevaSet` object.
`ids`	IDs to be selected for.
`id.name`	Names of the IDs.
`keep.batch`	Default `TRUE`. If `FALSE`, remove all other `model.ids` from the experiemt design that do not belong to selection.

Value

New Xeva object.

Examples

data(brca)
print(brca)
df <- subsetXeva(brca, ids = c("X-1004", "X-1008", "X-1286"), id.name="patient.id", keep.batch=TRUE)
print(df)
data(brca)
print(brca)
df <- subsetXeva(brca, ids = c("X-1004", "X-1008", "X-1286"), id.name="patient.id", keep.batch=TRUE)
print(df)

Summarize molecular profiles

Description

This function serves to get molecular profiles from a XevaSet object.

Usage

summarizeMolecularProfiles(
  object,
  drug,
  mDataType,
  tissue = NULL,
  sensitivity.measure = NULL,
  unique.model = TRUE,
  batch = NULL
)
summarizeMolecularProfiles(
  object,
  drug,
  mDataType,
  tissue = NULL,
  sensitivity.measure = NULL,
  unique.model = TRUE,
  batch = NULL
)

Arguments

`object`	The `XevaSet`.
`drug`	Name of the drug.
`mDataType`	`character`, where one of the molecular data types is needed.
`tissue`	Default `NULL` will return all tissue types.
`sensitivity.measure`	Default `NULL` will return all sensitivity measures.
`unique.model`	Default `TRUE` will return only one sequncing ID, in the case where one model ID maps to several sequencing IDs.
`batch`	Name of the batch. Default `NULL`.

Details

If a sequencing sample belongs to multiple models, summarizeMolecularProfiles will create a separate column for each model.
All models without molecular data will be removed from the output ExpressionSet.

Value

An ExpressionSet where sample names are model.id and sensitivity measures will be presented in pData.

Examples

data(brca)
pacRNA <- summarizeMolecularProfiles(brca, drug="paclitaxel", mDataType="RNASeq",
                                     tissue= "BRCA", sensitivity.measure="mRECIST")
print(pacRNA)
data(brca)
pacRNA <- summarizeMolecularProfiles(brca, drug="paclitaxel", mDataType="RNASeq",
                                     tissue= "BRCA", sensitivity.measure="mRECIST")
print(pacRNA)

Summarize Response of PDXs

Description

This function summarizes the drug response information of PDXs.

Usage

summarizeResponse(
  object,
  response.measure = "mRECIST",
  model.id = NULL,
  batch.id = NULL,
  group.by = "patient.id",
  summary.stat = c(";", "mean", "median"),
  tissue = NULL
)
summarizeResponse(
  object,
  response.measure = "mRECIST",
  model.id = NULL,
  batch.id = NULL,
  group.by = "patient.id",
  summary.stat = c(";", "mean", "median"),
  tissue = NULL
)

Arguments

`object`	The `XevaSet` object.
`response.measure`	`character` indicating which response measure to use. Use the `responseMeasures` function to find out what measures are available for each `XevaSet`.
`model.id`	The `model.id` for which data is required.
`batch.id`	A `vector` of batch names. Default `NULL` will return all batches.
`group.by`	Default `patient.id`. Dictates how the models should be grouped together. See details below.
`summary.stat`	Dictates which summary method to use if multiple IDs are found.
`tissue`	Name of the tissue. Default `NULL`

Details

There can be two types of drug response measure.

Per model response: One response value for each Model, eg. mRECIST_recomputed for each model.
Per batch response: One response value for each Batch, eg. angle between treatment and control groups.

For the per model response output, columns will be model.id (or group.by). For the per batch response output, the group.by value can be "batch.name".

Value

A matrix with rows as drug names, column as group.by. Each cell contains response.measure for the pair.

Examples

data(brca)
brca.mR <- summarizeResponse(brca, response.measure = "mRECIST", group.by="patient.id")

data(brca)
brca.mR <- summarizeResponse(brca, response.measure = "mRECIST", group.by="patient.id")

tumor growth inhibition (TGI) Computes the tumor growth inhibition (TGI) between two time-volume curves

Description

tumor growth inhibition (TGI) Computes the tumor growth inhibition (TGI) between two time-volume curves

Usage

TGI(contr.volume, treat.volume)
TGI(contr.volume, treat.volume)

Arguments

`contr.volume`	Volume vector for control
`treat.volume`	Volume vector for treatment

Value

Returns batch response object

Examples

contr.volume <- c(1.35, 6.57, 13.94, 20.39, 32.2, 39.26, 46.9, 53.91)
treat.volume <- c(0.4, 1.26, 2.59, 3.62, 5.77, 6.67, 7.47, 8.98, 9.29, 9.44)
TGI(contr.volume, treat.volume)

contr.volume <- c(1.35, 6.57, 13.94, 20.39, 32.2, 39.26, 46.9, 53.91)
treat.volume <- c(0.4, 1.26, 2.59, 3.62, 5.77, 6.67, 7.47, 8.98, 9.29, 9.44)
TGI(contr.volume, treat.volume)

waterfall plot Creates waterfall plot for a given drug.

Description

waterfall plot Creates waterfall plot for a given drug.

Usage

waterfall(
  object,
  res.measure,
  drug = NULL,
  group.by = NULL,
  summary.stat = c(";", "mean", "median"),
  tissue = NULL,
  model.id = NULL,
  model.type = NULL,
  type.color = "#cc4c02",
  legend.name = NULL,
  yname = NULL,
  title = NULL,
  sort = TRUE
)
waterfall(
  object,
  res.measure,
  drug = NULL,
  group.by = NULL,
  summary.stat = c(";", "mean", "median"),
  tissue = NULL,
  model.id = NULL,
  model.type = NULL,
  type.color = "#cc4c02",
  legend.name = NULL,
  yname = NULL,
  title = NULL,
  sort = TRUE
)

Arguments

`object`	The `XevaSet` object
`res.measure`	PDX model drug response measure
`drug`	Name of the drug
`group.by`	Group drug response data
`summary.stat`	How to summarize multiple values
`tissue`	Tissue type
`model.id`	Indicates which `model.id` to plot. Default `NULL` will plot all models
`model.type`	Type of model, such as mutated or wild type
`type.color`	A list with colors used for each type in the legend
`legend.name`	Name of the legend
`yname`	Name for the y-axis
`title`	Title of the plot
`sort`	Default `TRUE` will sort the data

Value

waterfall plot in ggplot2

Examples

data(brca)
waterfall(brca, drug="binimetinib", res.measure="best.avg.response_published")
## example with model.type where we color the models by TP53 mutation type
mut <- summarizeMolecularProfiles(brca,drug = "binimetinib", mDataType="mutation")
model.type <- Biobase::exprs(mut)["TP53", ]
waterfall(brca, drug="binimetinib", res.measure="best.avg.response_published",
          tissue="BRCA", model.id=names(model.type), model.type= model.type)

data(brca)
waterfall(brca, drug="binimetinib", res.measure="best.avg.response_published")
## example with model.type where we color the models by TP53 mutation type
mut <- summarizeMolecularProfiles(brca,drug = "binimetinib", mDataType="mutation")
model.type <- Biobase::exprs(mut)["TP53", ]
waterfall(brca, drug="binimetinib", res.measure="best.avg.response_published",
          tissue="BRCA", model.id=names(model.type), model.type= model.type)

Package 'Xeva'

Help Index

area between curves Computes the area between two time-volume curves.

Description

Usage

Arguments

Value

Examples

Add a new experimental design

Description

Usage

Arguments

Value

Examples

compute angle Computes the angle between two time-volume curves.

Description

Usage

Arguments

Value

Examples

area under the curve AUC Returns area under the curve

Description

Usage

Arguments

Value

Examples

Get batch information

Description

Usage

Arguments

Details

Value

Examples

PDXE breast cancer dataset

Description

Usage

Format

Source

XevaSet constructor

Description

Usage

Arguments

Details

Value

Examples

plot dose data

Description

Usage

Arguments

Value

Examples

Download a XevaSet object or table of available XevaSet objects

Description

Usage

Arguments

Value

Examples

Get drug information Get the drug information slot from a XevaSet object.

Description

Usage

Arguments

Value

Examples

get drug sensitivity values

Description

Usage

Arguments

Details

Value

Examples

Get PDX experiment data

Description

Usage

Arguments

Value

Examples

Get molecular profiles from a XevaSet object

Description

Usage

Arguments

area under the curve `AUC` Returns area under the curve