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.

Author(s)

Maintainer: Junwei Han hanjunwei1981@163.com

Authors:

• Baotong Zheng btzheng1116@163.com

Other contributors:

• Siyao Liu liusiyao29@163.com [contributor]

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

Value

Key dysfunctional subpathways in each pathway, in which the risk score of the genes were significantly higher.

Examples

require(graphite)
zz<-GetExampleData("zzz")
k<-FindSubPath(zz)

Get the example data

Description

Get the example data of test package for litte trials.

Usage

GetExampleData(exampleData)

Arguments

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.

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
)

Arguments

Value

the statistical significance p value and FDR for these optimal subpathways

Examples

require(graphite)
keysubpathways<-GetExampleData("keysubpathways")
zzz<-GetExampleData("zzz")
Permutation(keysubpathways,zzz,nperm1=10,method1=TRUE,nperm2=10,method2=FALSE)

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

Value

Network graph

Examples

require(graphite)

subpID<-unlist(strsplit("ACSS1/ALDH3B2/ADH1B/ADH1A/ALDH2/DLAT/ACSS2","/"))
pathway.name="Glycolysis / Gluconeogenesis"
zzz<- GetExampleData("zzz")
PlotSubpathway(subpID=subpID,pathway.name=pathway.name,zz=zzz)

combinep_three

Description

'combinep_three' combine three kinds of p-values,then,calculate z-score for them.

Usage

combinep_three(p1, p2, p3)

Arguments

Value

A numeric vector of z_scores

Examples

exp.p<-GetExampleData("exp.p")
meth.p<-GetExampleData("meth.p")
cnv.p<-GetExampleData("cnv.p")
combinep_three(exp.p,meth.p,cnv.p)

combinep_two

Description

'combinep_two' combine two kinds of p-values,then,calculate z-score for them.

Usage

combinep_two(p1, p2)

Arguments

Value

A numeric vector of z_scores

Examples

exp.p<-GetExampleData("exp.p")
meth.p<-GetExampleData("meth.p")
combinep_two(exp.p,meth.p)

coverp2zscore

Description

'coverp2zscore' calculate z-scores for p-values

Usage

coverp2zscore(pdata)

Arguments

Value

A numeric vector of z_scores

Examples

exp.p<-GetExampleData("exp.p")
meth.p<-GetExampleData("meth.p")
cnv.p<-GetExampleData("cnv.p")
coverp2zscore(exp.p)
coverp2zscore(meth.p)
coverp2zscore(cnv.p)

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

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,cnv.p,label1,label2,subpathdata,opt_subpathways

Author(s)

Junwei Hanhanjunwei1981@163.com,Baotong Zhengbtzheng1116@163.com,Siyao Liu liusiyao29@163.com

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

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"))
getCnvp(exp_data,cnv_data,amp_gene,del_gene,p.adjust=FALSE,method="fdr")

getExpp

Description

'getExpp' perform t-test on Expression profile data

Usage

getExpp(exp_data, label, p.adjust = TRUE, method = "fdr")

Arguments

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")
getExpp(profile,label,p.adjust=FALSE)

getMethp

Description

'getMethp' perform t-test on Methylation profile data

Usage

getMethp(meth_data, label, p.adjust = TRUE, method = "fdr")

Arguments

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

Examples

profile<-GetExampleData("meth_data")
label<-GetExampleData("label2")
getMethp(profile,label,p.adjust=FALSE)

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

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")
optsubpath<-opt_subpath(subpathdata,zz,overlap=0.6)