Manual
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Package ‘ICDS’
January 17, 2019
Type Package
Title Identification of Cancer Dysfunctional Sub-
pathway 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 <hanjunwei1981@163.com>
Description Identify Cancer Dysfunctional Sub-pathway by integrating gene expression, DNA methy-
lation and copy number variation, and pathway topological information. 1)We firstly calcu-
late the gene risk scores by integrating three kinds of data: DNA methylation, copy number vari-
ation, and gene expression. 2)Secondly, we perform a greedy search algorithm to identi-
fy the key dysfunctional sub-pathways within the pathways for which the discriminative s-
cores were locally maximal. 3)Finally, the permutation test was used to calculate statistical sig-
nificance 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
Rtopics documented:
ICDS-package........................................ 2
combinep_three....................................... 2
combinep_two........................................ 3
coverp2zscore........................................ 3
1
2combinep_three
envData ........................................... 4
FindSubPath......................................... 4
getCnvp ........................................... 5
GetExampleData ...................................... 6
getExpp ........................................... 6
getMethp .......................................... 7
opt_subpath......................................... 8
Permutation......................................... 8
PlotSubpathway....................................... 9
Index 10
ICDS-package Identification of Cancer Dysfunctional Subpathway by integrating D-
NA 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 ex-
pression. 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
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 the p-values or corrected p-values
p2 the p-values or corrected p-values
p3 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 A numeric vector of p-values or corrected p-values
p2 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)
4FindSubPath
envData The variables in the environment include an example expression pro-
file,an methylation profile,an copy number variation data,amplified
genes,deleted genes,A numeric vector of z_scores,p-values,A vec-
tor of 0/1s, indicating the class of samples,interested subpath-
ways,Optimized subpathway,and the statistical significance p value
and FDR for these optimal subpathways
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 ex-
pression. 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
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,cnv.p,label1,label2,subpathdata,opt_subpathways
Author(s)
Junwei Han<hanjunwei1981@163.com>,Baotong Zheng<btzheng1116@163.com>,Siyao Liu <liusiyao29@163.com>
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 A numeric vector of z_scores.
Pathway The name of the pathway database.
delta Diffusion coefficient in each step of searching subpath.
seed_p Define gene whose p-value smaller than seed_p as seed gene.
min.size The smallest size of subpathways.
out.F Logical,tell if output subpathways.
out.file file name of subpathways.
getCnvp 5
Value
Key dysfunctional subpathways in each pathway, in which the risk score of the genes were signifi-
cantly 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", "bon-
ferroni", "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")
6getExpp
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 knowl-
edgebased 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 row-
names 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", "bon-
ferroni", "BH", "BY",
getMethp 7
Details
For a given expression 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 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", "bon-
ferroni", "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
8Permutation
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 Optimize intersted subpathways
zz a vector of z-scores
nperm1 times of permutation to perform use method1
method1 permutation analysis method1
nperm2 times of permutation to perform use method2
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 gene list of a interested subpathway
pathway.name name of the interested subpathway
zz z-score of each gene
Pathway the name of the pathway database
layout 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
