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Package ‘ICDS’
January 17, 2019
Type Package
Title Identification of Cancer Dysfunctional Subpathway by integrating DNA methylation, copy number variation, and gene expression data
Version 0.1.0
Author Junwei Han,Baotong Zheng,Siyao Liu
Maintainer Junwei Han 
Description Identify Cancer Dysfunctional Sub-pathway by integrating gene expression, DNA methylation and copy number variation, and pathway topological information. 1)We firstly calculate the gene risk scores by integrating three kinds of data: DNA methylation, copy number variation, and gene expression. 2)Secondly, we perform a greedy search algorithm to identify the key dysfunctional sub-pathways within the pathways for which the discriminative scores were locally maximal. 3)Finally, the permutation test was used to calculate statistical significance level for these key dysfunctional sub-pathways.
License GPL (>= 2)
Encoding UTF-8
LazyData true
Suggests knitr,
rmarkdown,
prettydoc
VignetteBuilder knitr
Imports igraph,
graphite,
metap,
methods,
org.Hs.eg.db
Depends R (>= 2.10)
Roxygen list(markdown = TRUE)
RoxygenNote 6.1.1

R topics documented:
ICDS-package .
combinep_three
combinep_two .
coverp2zscore .

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2
2
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2

combinep_three
envData . . . . .
FindSubPath . . .
getCnvp . . . . .
GetExampleData
getExpp . . . . .
getMethp . . . .
opt_subpath . . .
Permutation . . .
PlotSubpathway .

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Index
ICDS-package

4
4
5
6
6
7
8
8
9
10

Identification of Cancer Dysfunctional Subpathway by integrating DNA methylation, copy number variation, and gene expression data

Description
Identify Cancer Dysfunctional Subpathway by integrating gene expression, DNA methylation and
copy number variation, and pathway topological information. 1)We firstly calculate the gene risk
scores by integrating three kinds of data: DNA methylation, copy number variation, and gene expression. 2)Secondly, we perform a greedy search algorithm to identify the key dysfunctional subpathways within the pathways for which the discriminative scores were locally maximal. 3)Finally,
the permutation test was used to calculate statistical significance level for these key dysfunctional
subpathways.

combinep_three

combinep_three

Description
combinep_three combine three kinds of p-values,then,calculate z-score for them.
Usage
combinep_three(p1, p2, p3)
Arguments
p1
p2
p3

the p-values or corrected p-values
the p-values or corrected p-values
the p-values or corrected p-values

Value
A numeric vector of z_scores
Examples
exp.p<-GetExampleData("exp.p")
meth.p<-GetExampleData("meth.p")
cnv.p<-GetExampleData("cnv.p")
## Not run: combinep_three(exp.p,meth.p,cnv.p)

combinep_two

3

combinep_two

combinep_two

Description
combinep_two combine two kinds of p-values,then,calculate z-score for them.
Usage
combinep_two(p1, p2)
Arguments
p1
p2

A numeric vector of p-values or corrected p-values
A numeric vector of p-values or corrected p-values

Value
A numeric vector of z_scores
Examples
exp.p<-GetExampleData("exp.p")
meth.p<-GetExampleData("meth.p")
## Not run: combinep_two(exp.p,meth.p)

coverp2zscore

coverp2zscore

Description
coverp2zscore calculate z-scores for p-values
Usage
coverp2zscore(pdata)
Arguments
pdata

A numeric vector of p-values or corrected p-values

Value
A numeric vector of z_scores
Examples
exp.p<-GetExampleData("exp.p")
meth.p<-GetExampleData("meth.p")
cnv.p<-GetExampleData("cnv.p")
## Not run: coverp2zscore(exp.p)
## Not run: coverp2zscore(meth.p)
## Not run: coverp2zscore(cnv.p)

4

FindSubPath

The variables in the environment include an example expression profile,an methylation profile,an copy number variation data,amplified
genes,deleted genes,A numeric vector of z_scores,p-values,A vector of 0/1s, indicating the class of samples,interested subpathways,Optimized subpathway,and the statistical significance p value
and FDR for these optimal subpathways

envData

Description
Identify Cancer Dysfunctional Subpathway by integrating gene expression, DNA methylation and
copy number variation, and pathway topological information. 1)We firstly calculate the gene risk
scores by integrating three kinds of data: DNA methylation, copy number variation, and gene expression. 2)Secondly, we perform a greedy search algorithm to identify the key dysfunctional subpathways within the pathways for which the discriminative scores were locally maximal. 3)Finally,
the permutation test was used to calculate statistical significance level for these key dysfunctional
subpathways.
Format
An environment variable
Details

The environment variable includes the variable exp_data, meth_data,cnv_data,amp_gene,del_gene,zzz,exp.p,meth.p
Author(s)
Junwei Han,Baotong Zheng,Siyao Liu 

FindSubPath

FindSubPath

Description
FindSubPath uses a greedy search algorithm to search for key subpathways in each entire pathway.
Usage
FindSubPath(zz, Pathway = "kegg", delta = 0.05, seed_p = 0.05,
min.size = 5, out.F = FALSE, out.file = "Subpath.txt")
Arguments
zz
Pathway
delta
seed_p
min.size
out.F
out.file

A numeric vector of z_scores.
The name of the pathway database.
Diffusion coefficient in each step of searching subpath.
Define gene whose p-value smaller than seed_p as seed gene.
The smallest size of subpathways.
Logical,tell if output subpathways.
file name of subpathways.

getCnvp

5

Value
Key dysfunctional subpathways in each pathway, in which the risk score of the genes were significantly higher.
Examples
require(graphite)
zz<-GetExampleData("zzz")
## Not run: k<-FindSubPath(zz)

getCnvp

getCnvp

Description
getCnvp perform t-test on copy number variation data
Usage
getCnvp(exp_data, cnv_data, amp_gene, del_gene, p.adjust = TRUE,
method = "fdr")
Arguments
exp_data

A data frame

cnv_data

Copy number variation data

amp_gene

A vector of strings, the IDs of amplified genes.

del_gene

A vector of strings, the IDs of deleted genes.

p.adjust

Logical,tell if returns corrected p-values

method

Correction method,which can be one of "holm", "hochberg", "hommel", "bonferroni", "BH", "BY",

Details
cnv_data is TCGA level4 data.if p.adjust=TRUE,return corrected p-values,if p.adjust=FALSE,return
p-values
Value
A numeric vector of p-values or corrected p-values
Examples
exp_data<-GetExampleData("exp_data")
meth_data<-GetExampleData("meth_data")
cnv_data<-GetExampleData("cnv_data")
amp_gene<-GetExampleData("amp_gene")
del_gene<-GetExampleData(("del_gene"))
## Not run: getCnvp(exp_data,cnv_data,amp_gene,del_gene,p.adjust=FALSE,method="fdr")

6

getExpp

GetExampleData

Get the example data

Description
Get the example data of test package for litte trials.
Usage
GetExampleData(exampleData)
Arguments
exampleData

A character, should be one of "exp_data", "meth_data", "cnv_data", "amp_gene",
"del_gene" ,"label1","label2","zz","exp.p","meth.p","cnv.p"and "pathdata".

Details
The function getExampleData(ExampleData = "exp.p)") obtains a vector of lncRNAs confirmed to
be related with breast cancer. The function getExampleData(ExampleData = "Profile") obtains the
expression pr
References
Subramanian, A., Tamayo, P., Mootha, V.K., Mukherjee, S., Ebert, B.L., Gillette, M.A., Paulovich,
A., Pomeroy, S.L., Golub, T.R., Lander, E.S. et al. (2005) Gene set enrichment analysis: a knowledgebased approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci U S A,
102, 15545-15550.

getExpp

getExpp

Description
getExpp perform t-test on Expression profile data
Usage
getExpp(exp_data, label, p.adjust = TRUE, method = "fdr")
Arguments
exp_data

A data frame, the expression profile to calculate p-value for each gene, the rownames should be the symbol of genes.

label

A vector of 0/1s, indicating the class of samples in the expression profile, 0
represents case, 1 represents control.

p.adjust

Logical,tell if returns corrected p-values

method

Correction method,which can be one of "holm", "hochberg", "hommel", "bonferroni", "BH", "BY",

getMethp

7

Details
For a given expression profile of two conditions, ICDS package provide t-test method to calculate pvalues or corrected p-values(if p.adjust=TRUE,return corrected p-values,if p.adjust=FALSE,return
p-values.) for each genes. The row of the expression profile should be gene symbols and the column
of the expression profile should be names of samples. Samples should be under two conditions and
the label should be given as 0 and 1.
Value
A numeric vector of p-values or corrected p-values
Examples
profile<-GetExampleData("exp_data")
label<-GetExampleData("label1")
## Not run: getExpp(profile,label,p.adjust=FALSE)

getMethp

getMethp

Description
getMethp perform t-test on Methylation profile data
Usage
getMethp(meth_data, label, p.adjust = TRUE, method = "fdr")
Arguments
meth_data

A data frame, the Methylation profile to calculate p-value for each gene, the
rownames should be the symbol of genes.

label

label A vector of 0/1s, indicating the class of samples in the Methylation profile,
0 represents case, 1 represents control.

p.adjust

Logical,tell if returns corrected p-values

method

Correction method,which can be one of "holm", "hochberg", "hommel", "bonferroni", "BH", "BY",

Details
For a given Methylation profile of two conditions, ICDS package provide t-test method to calculate
p-values or corrected p-values(if p.adjust=TRUE,return corrected p-values,if p.adjust=FALSE,return
p-values.) for each genes. The row of the Methylation profile should be gene symbols and the
column of the Methylation profile should be names of samples. Samples should be under two
conditions and the label should be given as 0 and 1.
Value
A numeric vector of p-values or corrected p-values

8

Permutation

Examples
profile<-GetExampleData("meth_data")
label<-GetExampleData("label2")
## Not run: getMethp(profile,label,p.adjust=FALSE)

opt_subpath

opt_subpath

Description
opt_subpath Optimize interested subpathways.If the number of genes shared by the two pathways
accounted for more than the Overlap ratio of each pathway genes,then combine two pathways.
Usage
opt_subpath(subpathdata, zz, overlap = 0.6)
Arguments
subpathdata

interested subpathways

zz

a vector of z-scores

overlap

Overlap ratio of each two pathway genes

Value
Optimized subpathway:the number of genes shared by any two pathways accounted for less than
the Overlap ratio of each pathway genes.
Examples
zz<-GetExampleData("zzz")
subpathdata<-GetExampleData("subpathdata")
## Not run: optsubpath<-opt_subpath(subpathdata,zz,overlap=0.6)

Permutation

Permutation

Description
the permutation test method 1 and method 2 were used to calculate the statistical significance level
for these optimal subpathways.
Usage
Permutation(subpathwayz, zz, nperm1 = 1000, method1 = TRUE,
nperm2 = 1000, method2 = FALSE)

PlotSubpathway

9

Arguments
subpathwayz
zz
nperm1
method1
nperm2
method2

Optimize intersted subpathways
a vector of z-scores
times of permutation to perform use method1
permutation analysis method1
times of permutation to perform use method2
permutation analysis method2

Value
the statistical significance p value and FDR for these optimal subpathways
Examples
require(graphite)
keysubpathways<-GetExampleData("keysubpathways")
zzz<-GetExampleData("zzz")
## Not run: Permutation(keysubpathways,zzz,nperm1=10,method1=TRUE,nperm2=10,method2=FALSE)

PlotSubpathway

PlotSubpathway

Description
PlotSubpathway:plot a network graph when user input a list of gene
Usage
PlotSubpathway(subpID, pathway.name, zz, Pathway = "kegg",
layout = layout.fruchterman.reingold)
Arguments
subpID
pathway.name
zz
Pathway
layout

gene list of a interested subpathway
name of the interested subpathway
z-score of each gene
the name of the pathway database
The layout specification(layout_). It must be a call to a layout specification
function.

Value
Network graph
Examples
require(graphite)
subpID<-unlist(strsplit("G6PC/HK3/GPI/FBP1/ALDOA/G6PC2","/"))
pathway.name="Glycolysis / Gluconeogenesis"
zzz<- GetExampleData("zzz")
## Not run: PlotSubpathway(subpID=subpID,pathway.name=pathway.name,zz=zzz)

Index
∗Topic data
envData, 4
amp_gene (envData), 4
cnv.p (envData), 4
cnv_data (envData), 4
combinep_three, 2
combinep_two, 3
coverp2zscore, 3
del_gene (envData), 4
envData, 4
exp.p (envData), 4
exp_data (envData), 4
FindSubPath, 4
getCnvp, 5
GetExampleData, 6
getExpp, 6
getMethp, 7
ICDS (ICDS-package), 2
ICDS-package, 2
label1 (envData), 4
label2 (envData), 4
layout_, 9
meth.p (envData), 4
meth_data (envData), 4
opt_subpath, 8
opt_subpathways (envData), 4
Permutation, 8
PlotSubpathway, 9
subpathdata (envData), 4
zzz (envData), 4

10
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