Package 'SubtypeDrug'

Title: Prioritization of Candidate Cancer Subtype Specific Drugs
Description: A systematic biology tool was developed to prioritize cancer subtype-specific drugs by integrating genetic perturbation, drug action, biological pathway, and cancer subtype. The capabilities of this tool include inferring patient-specific subpathway activity profiles in the context of gene expression profiles with subtype labels, calculating differentially expressed subpathways based on cultured human cells treated with drugs in the 'cMap' (connectivity map) database, prioritizing cancer subtype specific drugs according to drug-disease reverse association score based on subpathway, and visualization of results (Castelo (2013) <doi:10.1186/1471-2105-14-7>; Han et al (2019) <doi:10.1093/bioinformatics/btz894>; Lamb and Justin (2006) <doi:10.1126/science.1132939>). Please cite using <doi:10.1093/bioinformatics/btab011>.
Authors: Xudong Han, Junwei Han, Chonghui Liu
Maintainer: Junwei Han <[email protected]>
License: GPL (>= 2)
Version: 0.1.6
Built: 2024-10-29 05:34:26 UTC
Source: https://github.com/hanjunwei-lab/subtypedrug

Help Index

SubtypeDrug internal function

Description

Infering patient-specific subpathway activity profiles.

Usage

AccumulateNormal(x_matrix, control_index)

Arguments

x_matrix

A subpathway activity profile. rows are subpathwyas, columns are samples.
control_index

A vector. In the sample of the subpathway activity profile, the position of control samples.

Details

AccumulateNormal

Value

A matrix.

Author(s)

Xudong Han, Junwei Han, Chonghui Liu

Examples

x<-matrix(c(1:10),ncol = 5)
x1<-AccumulateNormal(x,c(3,5))

SubtypeDrug internal function

Description

Calculate subpathway enrichment score.

Usage

CalculateSES(labels.list, correl.vector = NULL)

Arguments

labels.list

A vector of 0 and 1.
correl.vector

A vector. The weight value used to calculate the enrichment score.

Details

CalculateSES

Value

A vector.

Author(s)

Xudong Han, Junwei Han, Chonghui Liu

Examples

x<-CalculateSES(sample(c(0,1),10,replace = TRUE),c(1:10))

Color

Description

This variable stores the color data required by the program.

Usage

Colork

Format

A vector containing 73 values.

Examples

data(Colork)

Simulated result data

Description

The simulated result data of only two sample types is generated by the functional PrioSubtypeDrug.

Usage

Disease_drugs

Format

A list containing 8 variables. The variables are as follows:

  • Cacner Results table for cacner

  • SubpathwayMatrix Subpathway activity natrix

  • SampleInformation Cancer sample phenotypic information

  • Parameter Parameter of the function PrioSubtypeDrug

Examples

# data(Disease_drugs)

Correspondence table of drug label and drug ID in PubCham database

Description

A data frame for the drug and its corresponding PubCham database ID.

Usage

Drugs_CID

Format

A dataframe with drug label and CID. The variables are as follows:

  • Drugs Drug label

  • CID Drug ID in PubCham database

Examples

data(Drugs_CID)

Simulated gene expression data

Description

Simulated normalized gene expression profile data.

Usage

Geneexp

Format

A matrix with 3000 genes and 40 samples.

Examples

data(Geneexp)

Gene expression data for testing

Description

Simulated normalized gene expression profile data.

Usage

GeneexpT

Format

A matrix with 40 samples.

Examples

data(GeneexpT)

SubtypeDrug internal function

Description

Obtaining drug-disease reverse association score matrix.

Usage

getDrugMatrix(spw_matrix, drug_target_data, weighted.score)

Arguments

spw_matrix

A subpathway activity profile. rows are subpathwyas, columns are samples.
drug_target_data

A list. A list stores a collection of drug up- and down-regulated subpathways.
weighted.score

A binary value of 0 or 1. If the 'weighted.score' = 1, the drug reverse association score will be weighted by the subpathway activity.

Details

getDrugMatrix

Value

A matrix.

Author(s)

Xudong Han, Junwei Han, Chonghui Liu

Examples

require(GSVA)
Geneexp<-get("GeneexpT")
UserDS<-get("UserDST")
UserGS<-get("UserGST")
gsvapar <- gsvaParam(Geneexp, UserGS)
spw_matrix<-gsva(gsvapar)
x<-getDrugMatrix(spw_matrix,UserDS,weighted.score=FALSE)

SubtypeDrug internal function

Description

According to the parameters set by the user, the up-regulatory and down-regulatory subpathway data of drug is obtained.

Usage

getDrugSpw(
  drug_target_data,
  spw_matrix_rnames,
  drug.P.value.threshold,
  drug.min.sz,
  drug.max.sz
)

Arguments

drug_target_data

A list. A list stores a collection of drug up- and down-regulated subpathways.
spw_matrix_rnames

A vector. A vector consisting of row names of subpathway activity profile.
drug.P.value.threshold

A value. According to the threshold of the significant P value set by parameter 'drug.p.val.threshold', the drug up-regulation and down-regulatory subpathways were screened.
drug.min.sz

A numeric. The drug regulated subpathways intersects with the subpathways in the subpathway activity profile. Then drugs with less than 'drug.spw.min.sz' up- or down-regulated subpathways are removed.
drug.max.sz

A numeric. Similar to parameter 'drug.spw.min.sz', drugs with more than 'drug.spw.max.sz' up- or down-regulated subpathways are removed.

Details

getDrugSpw

Value

a list.

Author(s)

Xudong Han, Junwei Han, Chonghui Liu

Examples

require(GSVA)
Geneexp<-get("Geneexp")
UserGS<-get("UserGS")
UserDS<-get("UserDS")
spw_matrix<-gsva(Geneexp,UserGS,verbose=FALSE)
x<-getDrugSpw(UserDS,row.names(spw_matrix),0.05,1,100)

Get drug chemical structure diagram data

Description

'getDrugStructure()' outputs the chemical structure graph data of the drug or compound based on the input drug label by the user. The results can be visualized by the 'plot' function.

Usage

getDrugStructure(drug.label = "", main = "", sub = "")

Arguments

drug.label

A character string of drug label to determine which drug to use for visualization.
main

An overall title for the chemical structure graph.
sub

A sub title for the chemical structure graph.

Details

getDrugStructure

Value

A sdfset object.

Author(s)

Xudong Han, Junwei Han, Chonghui Liu

Examples

require(rvest)
require(ChemmineR)
# Plot the chemical structure of drug pirenperone.
# Chem_str<-getDrugStructure(drug.label="pirenperone.")
# plot(Chem_str)

SubtypeDrug internal function

Description

Determine if the package is loaded. If the package is not loaded, the program will prompt the user.

Usage

isPackageLoaded(name)

Arguments

name

A string. The name of the R package which determines whether it is loaded.

Details

isPackageLoaded

Value

A string, TRUE or FALSE.

Author(s)

Xudong Han, Junwei Han, Chonghui Liu

Examples

isPackageLoaded("pheatmap")

Plot a heat map of the normalized drug-disease reverse association scores for cancer samples

Description

According to the parameter setting, the function 'plotDScoreHeatmap()' displays the heat map of the normalized drug-disease reverse association score for the significant drugs.

Usage

plotDScoreHeatmap(
  data,
  subtype.label = "all",
  SDS = "all",
  E_Pvalue.th = 1,
  E_FDR.th = 0.05,
  S_Pvalue.th = 1,
  S_FDR.th = 0.001,
  show.rownames = TRUE,
  show.colnames = FALSE,
  color = colorRampPalette(c("#0A8D0A", "#F8F0EB", "red"))(190),
  subtype_colors = NA,
  drug_colors = NA,
  border_color = "grey60",
  cellwidth = NA,
  cellheight = NA,
  fontsize = 10,
  fontsize.row = 10,
  fontsize.col = 10,
  scale = "row"
)

Arguments

data

A list of result data generated by function 'PrioSubtypeDrug()'.
subtype.label

Character string indicates which sample of the cancer subtype was used to plot the heat map. If subtype.label = "all" (default), all cancer samples will be shown in the heat map.
SDS

A string indicates that the range of SDS is used for the heat map. if SDS="all" (default), the SDS will not be filtered. SDS="negative", only drugs with SDS<0 are used. SDS="positive", only drugs with SDS>0 are used.
E_Pvalue.th

A numeric.A threshold is used to filter the drug effected P value (default: 1).
E_FDR.th

A numeric.A threshold is used to filter the drug effected FDR (default: 0.05).
S_Pvalue.th

A numeric.A threshold is used to filter the Subtype specific P value (default: 1).
S_FDR.th

A numeric.A threshold is used to filter the Subtype specific P value (default: 0.001).
show.rownames

Boolean specifying if row names are be shown (default: TRUE).
show.colnames

Boolean specifying if column names are be shown (default: FALSE).
color

Vector of colors used in heatmap.
subtype_colors

Vector of colors is used to annotate the sample subtype. Its length should correspond to the number of sample subtypes.
drug_colors

Vector of colors is used to label subtype-specific drugs.
border_color

Color of cell borders on heatmap, use NA if no border should be drawn.
cellwidth

Individual cell width in points. If left as NA, then the values depend on the size of plotting window.
cellheight

Individual cell height in points. If left as NA, then the values depend on the size of plotting window.
fontsize

Base fontsize for the plot (default: 10).
fontsize.row

Fontsize for rownames (default: 10).
fontsize.col

Fontsize for colnames (default: 10).
scale

Character indicating if the values should be centered and scaled in either the row direction or the column direction, or none. Corresponding values are "row" (default), "column" and "none".

Details

plotDScoreHeatmap

Value

A heat map.

Author(s)

Xudong Han, Junwei Han, Chonghui Liu

Examples

require(pheatmap)
## Get the result data of PrioSubtypeDrug().
## The data is based on the simulated breast cancer subtype data.
Subtype_drugs<-get("Subtype_drugs")
## Heat map of all subtype-specific drugs.
#plotDScoreHeatmap(data=Subtype_drugs,E_Pvalue.th=0.05,
#                           S_Pvalue.th=0.05)
## Plot only Basal subtype-specific drugs.
plotDScoreHeatmap(Subtype_drugs,subtype.label="Basal",SDS="all",E_Pvalue.th=0.05,
                  E_FDR.t=1,S_Pvalue.th=0.05,S_FDR.th=1)

Plot heat map of the drug regulated subpathway activity score

Description

The 'plotDSpwHeatmap()' function plots a heat map of the subpathways that are regulated by specified drug and have differential expression between specified cancer subtype and normal.

Usage

plotDSpwHeatmap(
  data,
  drug.label = "",
  subtype.label = "",
  show.rownames = TRUE,
  show.colnames = TRUE,
  color = NA,
  phen_colors = NA,
  border_color = "grey60",
  cellwidth = NA,
  cellheight = NA,
  fontsize = 10,
  fontsize.row = 10,
  fontsize.col = 10,
  scale = "row"
)

Arguments

data

A list of result data generated by function 'PrioSubtypeDrug()'.
drug.label

A character string of drug labels to determine which drug to use for visualization.
subtype.label

Character string indicates which sample of the cancer subtype was used to plot the heat map.
show.rownames

Boolean specifying if row names are be shown.
show.colnames

Boolean specifying if column names are be shown.
color

Vector of colors used in heatmap.
phen_colors

Vector of colors is used to annotate the sample subtype and control sample.It should be assigned two colors.
border_color

Color of cell borders on heatmap, use NA if no border should be drawn.
cellwidth

Individual cell width in points. If left as NA, then the values depend on the size of plotting window.
cellheight

Individual cell height in points. If left as NA, then the values depend on the size of plotting window.
fontsize

Base fontsize for the plot (default: 10).
fontsize.row

Fontsize for rownames (default: 10).
fontsize.col

Fontsize for colnames (default: 10).
scale

Character indicating if the values should be centered and scaled in either the row direction or the column direction, or none. Corresponding values are "row", "column" and "none".

Details

plotDSpwHeatmap

Based on the input cancer subtype, the program draws a heat map of the drug regulated subpathway activity score. If the cancer subtype of input has sutype-specific drug score (SDS)<0, we can observe the drug upregulatory subpathway is lowly expressed in the cancer subtype samples and high in the normal samples; the drug downregulatory subpathway is highly expressed in the cancer subtype samples and low in the normal samples. This indicates that after the drug action, these subpathways activity is converted from the level of the cancer subtype into the level of normal. If the cancer subtype of input has sutype-specific drug score (SDS)>0, it is indicated that the drug action may promote the subpathway expression status of the cancer subtype.

Value

A heat map.

Author(s)

Xudong Han, Junwei Han, Chonghui Liu

Examples

require(pheatmap)
## Get the result data of PrioSubtypeDrug().
## The data is based on the simulated breast cancer subtype data.
Subtype_drugs<-get("Subtype_drugs")
plotDSpwHeatmap(data=Subtype_drugs,drug.label="pirenperone(1.02e-05M)",subtype.label="Basal")
##Visualize the results of only two types of samples.
Disease_drugs<-get("Disease_drugs")
plotDSpwHeatmap(data=Disease_drugs,drug.label="W-13(1e-05M)",subtype.label="Cancer")

Plot a global graph of the drug

Description

The 'plotGlobalGraph()' identifies the drug label entered by the user, and plots an integrated diagram including box plot of the normalized drug-disease reverse association scores, null distribution curves of significant P-value, and heat map of cancer subtype sample distribution.

Usage

plotGlobalGraph(
  data,
  drug.label = "",
  overall.main = "",
  overall.cex.main = 1.5,
  cex.submap.axis = 1,
  cex.submap.lab = 1,
  cex.submap.main = 1,
  cex.submap.sub = 1,
  cex.legend = 1
)

Arguments

data

A list of result data generated by function 'PrioSubtypeDrug()'.
drug.label

A character string of drug labels to determine which drug to use for visualization.
overall.main

An overall title for the whole graph. If the user does not make any input, the title will display a drug label.
overall.cex.main

The magnification to be used for overall.main (default: 1.5).
cex.submap.axis

The magnification to be used for axis of each submap annotation relative to the current setting of cex.
cex.submap.lab

The magnification to be used for x and y labels of each submap relative to the current setting of cex.
cex.submap.main

The magnification to be used for main titles of each submap relative to the current setting of cex.
cex.submap.sub

The magnification to be used for sub titles of each submap relative to the current setting of cex.
cex.legend

fontsize of labels for legend.

Details

plotGlobalGraph

Value

A plot.

Author(s)

Xudong Han, Junwei Han, Chonghui Liu

Examples

## Get the result data of PrioSubtypeDrug().
## The data is based on the simulated breast cancer subtype data.
Subtype_drugs<-get("Subtype_drugs")
## Plot a global graph of the drug pirenperone(1.02e-05M).
plotGlobalGraph(data=Subtype_drugs,drug.label="pirenperone(1.02e-05M)")

Polt a subpathway network graph

Description

Visualize a subpathway network graph.

Usage

plotSpwNetGraph(
  spwid,
  layout = NULL,
  margin = 0,
  vertex.label.cex = 0.6,
  vertex.label.font = 1,
  vertex.size = 8,
  vertex.size2 = 6,
  edge.arrow.size = 0.2,
  edge.arrow.width = 3,
  edge.label.cex = 0.6,
  vertex.label.color = "black",
  vertex.color = "#BFFFBF",
  vertex.frame.color = "dimgray",
  edge.color = "dimgray",
  edge.label.color = "dimgray",
  sub = NULL,
  main = NULL
)

Arguments

spwid

The subpathway id which the user wants to plot.
layout

A matrix of x-y coordinates with two dims. Determine the placement of the nodes for drawing a graph.
margin

A numeric. The value is usually between -0.5 and 0.5, which is able to zoom in or out a subpathway graph. The default is 0.
vertex.label.cex

A numeric vector of node label size.
vertex.label.font

A numeric vector of label font.
vertex.size

A numeric vector of Node size. See plot.igraph.
vertex.size2

A numeric vector of Node size.
edge.arrow.size

Edge arrow size.The default is 0.2.
edge.arrow.width

Edge arrow width. The default is 3.
edge.label.cex

Edge label size.
vertex.label.color

A vector of node label colors. The default is black.
vertex.color

A vector of node colors. The default is the KEGG node color.
vertex.frame.color

A vector of node frame color. The default is dimgray.
edge.color

A vector of edge color. The default is dimgray.
edge.label.color

A vector of edge label color. The default is dimgray.
sub

A character string of subtitle.
main

A character string of main title.

Details

plotSpwNetGraph

The function plotSpwNetGraph is able to display a subpathway graph. The argument layout is used to determine the placement of the nodes for drawing a graph.The layouts provided in igraph include 'layout_as_star', 'layout_as_tree', 'layout_in_circle', 'layout_nicely','layout_on_grid', 'layout_on_sphere', 'layout_randomly', 'layout_with_dh', 'layout_with_fr', 'layout_with_gem', 'layout_with_graphopt', 'layout_with_kk', 'layout_with_lgl', 'layout_with_mds'. The 'layout_as_tree' generates a tree-like layout, so it is mainly for trees. The 'layout_randomly' places the nodes randomly. The 'layout_in_circle' places the nodes on a unit circle. Detailed information on the parameters can be found in layout_

Value

a plot

Author(s)

Xudong Han, Junwei Han, Chonghui Liu

Examples

require(igraph)
# plot network graph of the subpathway 00020_4.
plotSpwNetGraph(spwid="00020_4")

Prioritization of candidate cancer subtype-specific drugs (PrioSubtypeDrug)

Description

Integrating drug, gene, and subpathway data to identify drugs specific to cancer subtypes.

Usage

PrioSubtypeDrug(
  expr,
  input.cls = "",
  control.label = "",
  subpathway.list,
  spw.min.sz = 10,
  spw.max.sz = Inf,
  spw.score.method = "gsva",
  kcdf = "Gaussian",
  drug.spw.data,
  drug.spw.p.val.th = 0.05,
  drug.spw.min.sz = 10,
  drug.spw.max.sz = Inf,
  weighted.drug.score = TRUE,
  nperm = 1000,
  parallel.sz = 1,
  E_FDR = 0.05,
  S_FDR = 0.001
)

Arguments

expr

Matrix of gene expression values (rows are genes, columns are samples).
input.cls

Input sample subtype class vector file in CLS format.
control.label

In the CLS file of 'input.cls', the label of the control sample.
subpathway.list

A list. The subpathway list data is mined from KEGG data is stored in the package 'SubtypeDrugData' and can be downloaded through the connection https://github.com/hanjunwei-lab/SubtypeDrugData. The gene tags included in the subpathway list data should be consistent with those in the gene expression profile. The package 'SubtypeDrugData' provides two choices that include the Entrezid and Symbol tags of the gene. Users can also enter their own pathway or gene set list data.
spw.min.sz

Removes subpathways that contain fewer genes than 'spw.min.sz' (default: 10).
spw.max.sz

Removes subpathways that contain more genes than 'spw.max.sz' (default: Inf).
spw.score.method

Method to employ in the estimation of subpathway enrichment scores per sample. By default this is set to 'gsva' (Hänzelmann et al, 2013) and other options are 'ssgsea' (Barbie et al, 2009).
kcdf

Character string denoting the kernel to use during the non-parametric estimation of the cumulative distribution function of expression levels across samples when 'spw.score.method="gsva"'. By default, 'kcdf="Gaussian"' which is suitable when input expression values are continuous, such as microarray fluorescent units in logarithmic scale, RNA-seq log-CPMs, log-RPKMs or log-TPMs. When input expression values are integer counts, such as those derived from RNA-seq experiments, then this argument should be set to 'kcdf="Poisson"'.
drug.spw.data

A list data of drug regulation. The drug subpathway association data we constructed is stored in package 'SubtypeDrugData' and can be downloaded via connection https://github.com/hanjunwei-lab/SubtypeDrugData. If the input is user-defined drug regulation data, the data should be a list data with each drug as its element. Each drug also contains 'Target_upregulation' and 'Target_downregulation' subpathway or gene set. Subpathway or gene set contained in drug regulation data should exist in input data of parameter 'subpathway.list'.
drug.spw.p.val.th

Parameter used only when 'drug.spw.data="DrugSpwData"'. According to the threshold of the significant P value set by parameter 'drug.spw.p.val.th' (default: 0.05), the drug up-regulation and down-regulatory subpathways were screened.
drug.spw.min.sz

A numeric. The drug regulated subpathways intersects with the subpathways in the subpathway activity profile. Then drugs with less than 'drug.spw.min.sz' (default: 10) up- or down-regulated subpathways are removed.
drug.spw.max.sz

A numeric. Similar to parameter 'drug.spw.min.sz', drugs with more than 'drug.spw.max.sz' (default: Inf) up- or down-regulated subpathways are removed.
weighted.drug.score

A boolean values determines the method for calculating the normalized drug-disease reverse association score of the drug for each sample. 'weighted.drug.score=TRUE' (default): KS random walk statistic with individualized subpathway activity aberrance score as weight was used to calculate the normalized drug-disease reverse association score. 'weighted.drug.score=FALSE': Similar to 'CMap' (Lamb et al., 2006), no weight is needed, and the normalized drug-disease reverse association score is calculated by the rank of the individualized subpathway activity aberrance score.
nperm

Number of random permutations (default: 1000).
parallel.sz

Number of processors to use when doing the calculations in parallel (default value: 1). If parallel.sz=0, then it will use all available core processors unless we set this argument with a smaller number.
E_FDR

Significance threshold for E_FDR for drugs (default: 0.05)
S_FDR

Significance threshold for S_FDR for drugs (default: 0.001)

Details

PrioSubtypeDrug

First, the function PrioSubtypeDrug uses the 'GSVA' or 'ssgsea' method to convert the disease gene expression profile into subpathway activity profile. Parameters 'subpathway.list', 'spw.min.sz' and 'spw.max.sz' are used to process the subpathway list data. 'spw.score.method' and 'kcdf' are used to control the method of constructing the subpathway activity score profile. Individualized subpathway activity aberrance score was estimated using the mean and standard deviation of the Control samples. Subpathways of each cancer sample are ordered in a ranked list according to individualized subpathway activity aberrance score. Next, we calculate the normalized drug-disease reverse association score by enriching drug regulated subpathway tags to the subpathway ranked list. Finlly, all drug-regulated subpathways are enriched into each cancer sample to obtain a normalized drug-disease reverse association score matrix. The 'drug.spw.p.val.th', 'drug.spw.min.sz' and 'drug.spw.max.sz' is used to screen the drug regulated subpathway set. If user-defined drug targeting data is used, drug regulated 'Target_upregulation' and 'Target_downregulation' should already be defined in the data. The 'weighted.drug.score' to control the method of calculating the normalized drug-disease reverse association score. Finally, empirical sample-based permutation test procedure to obtain significative cancer subtype specific drugs. For samples containing only cancer and Control, the subpathways are ranked according to the difference in activity between cancer and Control samples. Subsequently, the subpathway set of drug up- and down-regulated is enriched to the ranking list of subpathway to evaluate the normalized drug-disease reverse association score and subpathway-based permutation test procedure to calculate significance. The subpathway list data and drug subpathway associated data set is stored in package 'SubtypeDrugData' and can be obtained on https://github.com/hanjunwei-lab/SubtypeDrugData.

Value

A list contains the result table of drug scoring and significance, a subpathway activity score matrix, a normalized drug-disease reverse association score matrix, sample information, and user set parameter information.

Author(s)

Xudong Han, Junwei Han, Chonghui Liu

Examples

require(GSVA)
require(parallel)
## Get simulated breast cancer gene expression profile data.
Geneexp<-get("Geneexp")
## Obtain sample subtype data and calculate breast cancer subtype-specific drugs.
Subtype<-system.file("extdata", "Subtype_labels.cls", package = "SubtypeDrug")

## Subpathway list data and drug subpathway association data
## were stored in packet `SubtypeDrugData`.
## `SubtypeDrugData` has been uploaded to the github repository.
## If subpathway list data and drug subpathway association data are needed,
## users can download and install through `install_github` function and
## set parameter url=""hanjunwei-lab/SubtypeDrugData".
## After installing and loading package `SubtypeDrugData`,
## users can use the following command to get the data.
## Get subpathway list data.
## If the gene expression profile contains gene Symbol.
## data(SpwSymbolList)
## If the gene expression profile contains gene Entrezid.
## data(SpwEntrezidList)
## Get drug subpathway association data.
## data(DrugSpwData)

## Identify breast subtype-specific drugs.
## Subtype_drugs<-PrioSubtypeDrug(Geneexp,Subtype,"Control",SpwSymbolList,drug.spw.data=DrugSpwData,
##                                       E_FDR=1,S_FDR=1)

## Identify breast cancer-related drugs in only two types of samples: breast cancer and control.
Cancer<-system.file("extdata", "Cancer_normal_labels.cls", package = "SubtypeDrug")
## Disease_drugs<-PrioSubtypeDrug(Geneexp,Cancer,"Control",SpwSymbolList,drug.spw.data=DrugSpwData,
##                                       E_FDR=1,S_FDR=1)

## The function PrioSubtypeDrug() can also support user-defined data.
Geneexp<-get("GeneexpT")
## User-defined drug regulation data should resemble the structure below
UserDS<-get("UserDST")
str(UserDS)
## Need to load gene set data consistent with drug regulation data.
UserGS<-get("UserGST")
str(UserGS)
Drugs<-PrioSubtypeDrug(Geneexp,Cancer,"Control",UserGS,spw.min.sz=1,
                       drug.spw.data=UserDS,drug.spw.min.sz=1,
                       nperm=10,E_FDR=1,S_FDR=1)

SubtypeDrug internal function

Description

These are function read sample label file (.cls format).

Usage

ReadClsFile(file)

Arguments

file

Input sample subtype class vector file in CLS format.

Details

ReadClsFile

Value

a list

Author(s)

Xudong Han, Junwei Han, Chonghui Liu

Examples

Subtype<-system.file("extdata", "Subtype_labels.cls", package = "SubtypeDrug")
x<-ReadClsFile(Subtype)

Subpathway network structure data

Description

A list to store the network data of the genes contained in the subpathway.

Usage

SpwNetworkData

Format

A list containing 1598 subpathway network.

Examples

data(SpwNetworkData)

Simulation result data

Description

The result data of the simulation is generated by the functional OCSSD.

Usage

Subtype_drugs

Format

A list containing 8 variables. The variables are as follows:

  • Basal Results table for basal subtype

  • Her2 Results table for Her2 subtype

  • LumA Results table for LumA subtype

  • LumB Results table for LumB subtype

  • DrugMatrix Drug disease reverse association matrix

  • SubpathwayMatrix Subpathway activity natrix

  • SampleInformation Cancer sample phenotypic information

  • Parameter Parameter of the function OCSSD

Examples

# data(Subtype_drugs)

Simulated user-defined drug regulator subpathway dataset

Description

The drug regulator subpathway data set is modeled as a case.

Usage

UserDS

Format

A list containing 5 drugs.

Examples

data(UserDS)

User-defined drug regulator subpathway dataset for testing

Description

The drug regulator subpathway data set is modeled as a case.

Usage

UserDST

Format

A list.

Examples

data(UserDST)

Simulated user-defined gene set data

Description

Gene set data is simulated for case studies.

Usage

UserGS

Format

A list containing 50 gene sets.

Examples

data(UserDS)

User-defined gene set data for testing

Description

Gene set data is simulated for case studies.

Usage

UserGST

Format

A list.

Examples

data(UserGST)