| Type: | Package |
| Title: | Identification of Dysregulated MiRNAs Based on MiRNA-MiRNA Interaction Network |
| Version: | 0.1.0 |
| Maintainer: | Junwei Han <hanjunwei1981@163.com> |
| Description: | A systematic biology tool was developed to identify dysregulated miRNAs via a miRNA-miRNA interaction network. 'IDMIR' first constructed a weighted miRNA interaction network through integrating miRNA-target interaction information, molecular function data from Gene Ontology (GO) database and gene transcriptomic data in specific-disease context, and then, it used a network propagation algorithm on the network to identify significantly dysregulated miRNAs. |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| Encoding: | UTF-8 |
| LazyData: | true |
| Imports: | egg, fastmatch, forestplot, ggplot2, grDevices, grid, igraph, pheatmap, survival, survminer |
| RoxygenNote: | 7.2.3 |
| Depends: | R (≥ 2.10) |
| Suggests: | knitr, rmarkdown |
| VignetteBuilder: | knitr |
| NeedsCompilation: | no |
| Packaged: | 2023-11-09 11:34:00 UTC; 89800 |
| Author: | Junwei Han [aut, cre, cph], Xilong Zhao [aut], Jiashuo Wu [aut] |
| Repository: | CRAN |
| Date/Publication: | 2023-11-09 15:30:02 UTC |
GetData_Mirna
Description
Get the example data
Usage
GetData_Mirna(Data)
Arguments
Data |
A character should be one of"survival", "GEP", "MF_Target", "MiRNA_Target", "matrix_mirna_go_inter", "matrix_mirna_go_jaccard" |
Value
data
GetGDEscore
Description
Function "GetGDEscore" is used to calculate gene differential expression levels.
Usage
GetGDEscore(ExpData,Label)
Arguments
ExpData |
A gene expression profile of interest (rows are genes, columns are samples). |
Label |
A character vector consists of "0" and "1" which represent sample class in the gene expression profile. "0" means normal sample and "1" means disease sample. |
Value
A matrix with one column of GDEscore.
Examples
# Obtain the example data
GEP<-GetData_Mirna("GEP")
label<-GetData_Mirna("label")
# Run the function
GDEscore<-GetGDEscore(GEP,label)
IdentifyMiRNA
Description
The function "IdentifyMiRNA" is used to identify significantly dysregulated miRNAs by calculating the eigenvector centrality of miRNAs.
Usage
IdentifyMiRNA(GDEscore.table,nperm=1000,damping=0.90)
Arguments
GDEscore.table |
A matrix with one column of GDEscore. |
nperm |
The Number of random permutations (default: 100). |
damping |
Restart the probability of the random-walk algorithm (default: 0.9). |
Value
A data frame with seven columns those are "MiRNA", "Target", "Number" (number of targets), "Score" (Centrality score), "P-value", and "FDR".
Examples
# Obtain the example data
GEP<-GetData_Mirna("GEP")
label<-GetData_Mirna("label")
# Run the function
GDEscore<-GetGDEscore(GEP,label)
MiRNAScore<-IdentifyMiRNA(GDEscore,nperm=5, damping=0.90)
An environment variable that includes some example data
Description
An environment variable that includes some example data. matirx_mirna_go_inter:A matrix of Jaccard score between MiRNAs and GOMF. matirx_mirna_go_jaccard:A matrix consisting of genes shared by MiRNAs targets and GOMF. MiRNAScore:a ranked list of strong and weak associations with cancer. MF_Target:GOMF and corresponding targets. MiRNA_Target:MiRNAs and corresponding targets. zscore_BRCA:An example gene expression profile. label:A vector representing the label of the sample of BRCA, where "1" is the disease sample and "0" is the normal sample. survival:A dataframe including three columns which are sample, status, and time.
Usage
MirnaData
Format
An environment variable
MutiMiRNA_CRModel
Description
Function "MutiMiRNA_CRModel" can build a multivariate Cox model through integrating the models constructed separately based on different mirna targets.
Usage
MutiMiRNA_CRModel(ExpData, MiRNAs,SurvivalData,cutoff.point=NULL)
Arguments
ExpData |
A gene expression profile of interest (rows are genes, columns are samples). |
MiRNAs |
An interest miRNA vector. |
SurvivalData |
Survival data (the column names are: "sample", "status", and "time") corresponding to the samples in gene expression profile of interest. |
cutoff.point |
A numeric value used to divide high-risk and low-risk groups. |
Value
A list includes a data frame with seven parts those are "sample", "status", "time", "target gene expression", "risk score", "group", and a data frame with five columns those are "Gene", "HR", "HR.95L", "HR.95H", "beta", and "P-value".
Examples
# Obtain the example data
GEP<-GetData_Mirna("GEP")
survival<-GetData_Mirna("survival")
MiRNAs<-c("hsa-miR-21-5p","hsa-miR-26a-5p","hsa-miR-369-5p","hsa-miR-1238-3p","hsa-miR-10b-5p")
# Run the function
MutiMiRNA_CRData<-MutiMiRNA_CRModel(GEP,
MiRNAs,survival,cutoff.point=NULL)
PlotForest
Description
Function "PlotForest" can visualize the result of Cox regression analysis through forest plot.
Usage
PlotForest(MiRNA_CRData,g.pos = 2,b.size = 3,col = c("#FE0101", "#1C61B6", "#A4A4A4"),
lwd.zero = 2,lwd.ci = 3,x.lab = "Hazard Ratio Plot")
Arguments
MiRNA_CRData |
A list includes a data frame with seven parts those are "sample", "status", "time", "target genes expression", "risk score", "group", and a data frame with five columns those are "Gene", "HR", "HR.95L", "HR.95H", "beta", and "P-value". |
g.pos |
The position of the graph element within the table of text. The position can be 1-(ncol(labeltext) + 1). You can also choose set the position to "left" or "right". |
b.size |
Override the default box size based on precision. |
col |
Set the colors for all the elements in the plot. |
lwd.zero |
lwd for the vertical line that gives the no-effect line, see gpar. |
lwd.ci |
lwd for the confidence bands, see gpar. |
x.lab |
x-axis label. |
Value
Forest maps associated with the Cox risk model.
Examples
# Obtain the example data
GEP<-GetData_Mirna("GEP")
survival<-GetData_Mirna("survival")
MiRNAs<-c("hsa-miR-21-5p","hsa-miR-26a-5p","hsa-miR-369-5p","hsa-miR-1238-3p","hsa-miR-10b-5p")
# Run the function
SingleMiRNA_CRData<-SingleMiRNA_CRModel(GEP,
"hsa-miR-21-5p",survival,cutoff.point=NULL)
PlotForest(SingleMiRNA_CRData)
MutiMiRNA_CRData<-MutiMiRNA_CRModel(GEP,
MiRNAs,survival,cutoff.point=NULL)
PlotForest(MutiMiRNA_CRData)
PlotHeatmap
Description
The function "PlotHeatmap" is used to plot a heat map of miRNA targets expression.
Usage
PlotHeatmap(MiRNA_CRData,yaxis=c(-2,2),scale="row",
cluster.rows=FALSE,cluster.cols=FALSE,show.colnames=FALSE,
ann_colors=c("#ef6d6d","#5470c6"),col=c("#ef6d6d","#5470c6"))
Arguments
MiRNA_CRData |
A list includes a data frame with seven parts those are "sample", "status", "time", "target genes expression", "risk score", "group", and a data frame with five columns those are "Gene", "HR", "HR.95L", "HR.95H", "beta", and "P-value". |
yaxis |
The upper and lower limits of this heat map. |
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". |
cluster.rows |
A logical value that represents whether row clustering is used. |
cluster.cols |
A logical value that represents whether col clustering is used. |
show.colnames |
This parameter controls whether column names are displayed. |
ann_colors |
Vector of colors used to define groups. |
col |
Vector of colors used in the heatmap. |
Value
A heat map of miRNA targets expression.
Examples
# Obtain the example data
GEP<-GetData_Mirna("GEP")
survival<-GetData_Mirna("survival")
MiRNAs<-c("hsa-miR-21-5p","hsa-miR-26a-5p","hsa-miR-369-5p","hsa-miR-1238-3p","hsa-miR-10b-5p")
# Run the function
SingleMiRNA_CRData<-SingleMiRNA_CRModel(GEP,
"hsa-miR-21-5p",survival,cutoff.point=NULL)
PlotHeatmap(SingleMiRNA_CRData)
MutiMiRNA_CRData<-MutiMiRNA_CRModel(GEP,
MiRNAs,survival,cutoff.point=NULL)
PlotHeatmap(MutiMiRNA_CRData)
PlotScatter
Description
Function "PlotScatter" is used to plot a scatter diagram.
Usage
PlotScatter(MiRNA_CRData,status.0='Alive',status.1='Dead',
TitleYlab_A='Risk Score',TitleYlab_B='Survival Time',TitleXlab='Rank',
TitleLegend_A='Risk Group',TitleLegend_B='Status',
color.A=c(low='blue',high='red'),color.B=c(status.0='blue',status.1='red'))
Arguments
MiRNA_CRData |
A list includes a data frame with seven parts those are "sample", "status", "time", "target genes expression", "risk score", "group", and a data frame with five columns those are "Gene", "HR", "HR.95L", "HR.95H", "beta", and "P-value". |
status.0 |
string. Code for event 0. Default is 'Alive' |
status.1 |
string. Code for event 1. Default is 'Dead' |
TitleYlab_A |
string, y-lab title for figure A. Default is 'Riskscore' |
TitleYlab_B |
string, y-lab title for figure B. Default is 'Survival Time' |
TitleXlab |
string, x-lab title for figure B. Default is 'Rank' |
TitleLegend_A |
string, legend title for figure A. Default is 'Risk Group' |
TitleLegend_B |
string, legend title for figure B. Default is 'Status' |
color.A |
color for figure A. Default is low = 'blue', high = 'red' |
color.B |
color for figure B. Default is status.0 = 'blue', status.1 = 'red' |
Value
A riskscore picture
Examples
# Obtain the example data
GEP<-GetData_Mirna("GEP")
survival<-GetData_Mirna("survival")
MiRNAs<-c("hsa-miR-21-5p","hsa-miR-26a-5p","hsa-miR-369-5p","hsa-miR-1238-3p","hsa-miR-10b-5p")
# Run the function
SingleMiRNA_CRData<-SingleMiRNA_CRModel(GEP,
"hsa-miR-21-5p",survival,cutoff.point=NULL)
PlotScatter(SingleMiRNA_CRData)
MutiMiRNA_CRData<-MutiMiRNA_CRModel(GEP,
MiRNAs,survival,cutoff.point=NULL)
PlotScatter(MutiMiRNA_CRData)
PlotSurvival
Description
Function "PlotSurvival" is used to draw a Kaplan-Meier curve.
Usage
PlotSurvival(MiRNA_CRData,colors=c("#ef6d6d","#5470c6"))
Arguments
MiRNA_CRData |
A list includes a data frame with seven parts those are "sample", "status", "time", "target genes expression", "risk score", "group", and a data frame with five columns those are "Gene", "HR", "HR.95L", "HR.95H", "beta", and "P-value". |
colors |
Vector of colors used to define groups. |
Value
A survival curve of a data set.
Examples
# Obtain the example data
GEP<-GetData_Mirna("GEP")
survival<-GetData_Mirna("survival")
MiRNAs<-c("hsa-miR-21-5p","hsa-miR-26a-5p","hsa-miR-369-5p","hsa-miR-1238-3p","hsa-miR-10b-5p")
# Run the function
SingleMiRNA_CRData<-SingleMiRNA_CRModel(GEP,
"hsa-miR-21-5p",survival,cutoff.point=NULL)
PlotSurvival(SingleMiRNA_CRData)
MutiMiRNA_CRData<-MutiMiRNA_CRModel(GEP,
MiRNAs,survival,cutoff.point=NULL)
PlotSurvival(MutiMiRNA_CRData)
SingleMiRNA_CRModel
Description
Function "SingleMiRNA_CRModel" uses survival data to build a multivariate Cox model using the targets of a single miRNA.
Usage
SingleMiRNA_CRModel(ExpData,MiRNA,cutoff.point=NULL,SurvivalData)
Arguments
ExpData |
A gene expression profile of interest (rows are genes, columns are samples). |
MiRNA |
A miRNA ID. |
cutoff.point |
A numeric value is used to divide high-risk and low-risk groups. |
SurvivalData |
Survival data (the column names are: "sample", "status", "time") corresponding to samples in the gene expression profile of interest. |
Value
A list includes a data frame with seven parts those are "sample", "status", "time", "target genes expression", "risk score", "group", and a dataframe with five columns those are "Gene", "HR", "HR.95L", "HR.95H", "beta", and "P-value".
Examples
# Obtain the example data
GEP<-GetData_Mirna("GEP")
survival<-GetData_Mirna("survival")
# Run the function
SingleMiRNA_CRData<-SingleMiRNA_CRModel(GEP,
"hsa-miR-21-5p",cutoff.point=NULL,survival)