| Title: | Predict Drug Functional Similarity to Drug Repurposing |
|---|---|
| Description: | A systematic biology tool was developed to repurpose drugs via a drug-drug functional similarity network. 'DrugSim2DR' first predict drug-drug functional similarity in the context of specific disease, and then using the similarity constructed a weighted drug similarity network. Finally, it used a network propagation algorithm on the network to identify drugs with significant target abnormalities as candidate drugs. |
| Authors: | Junwei Han [aut, cre, cph], Ji Li [aut], Jiashuo Wu [aut] |
| Maintainer: | Junwei Han <[email protected]> |
| License: | GPL (>= 2) |
| Version: | 0.1.1 |
| Built: | 2024-10-27 03:35:05 UTC |
| Source: | https://github.com/hanjunwei-lab/drugsim2dr |
Function "CalDEscore" uses gene expression to calculate differential expression level.
CalDEscore(exp, Label)CalDEscore(exp, Label)
exp |
A gene expression profile of interest (rows are genes, columns are samples). |
Label |
A character vector consist of "0" and "1" which represent sample class in the gene expression profile. "0" means normal sample and "1" means disease sample. |
A matrix with one column of zscore.
# Obtain the example data GEP<-Gettest("GEP") label<-Gettest("label") # Run the function DEscore<-CalDEscore(GEP,label)# Obtain the example data GEP<-Gettest("GEP") label<-Gettest("label") # Run the function DEscore<-CalDEscore(GEP,label)
Easily generate custom data frame summaries
Maintainer: Junwei Han [email protected] [copyright holder]
Authors:
Ji Li
Jiashuo Wu
The function "DrugReposition" is used in drug repositioning by calculating the eigenvector centrality of drugs.
DrugReposition(DE,nperm = 1000,r = 0.9,p = 10^-10)DrugReposition(DE,nperm = 1000,r = 0.9,p = 10^-10)
DE |
A matrix with one column of zscore. |
nperm |
Number of random permutations (default: 1000). |
r |
Restart the probability of the random-walk algorithm (default: 0.9). |
p |
For each node, if the difference in centrality score between iterations changes less than this value, the algorithm considers the calculation complete (default: 10^-10). |
A dataframe with seven columns those are drugbankid, centralscore, p.value,fdr,number of targets, drug targets,drugname.
# Obtain the example data GEP<-Gettest("GEP") label<-Gettest("label") # Run the function DEscore<-CalDEscore(GEP,label) # Run the function drug_centrality<-DrugReposition(DE=DEscore,nperm = 1000,r = 0.9,p = 10^-10)# Obtain the example data GEP<-Gettest("GEP") label<-Gettest("label") # Run the function DEscore<-CalDEscore(GEP,label) # Run the function drug_centrality<-DrugReposition(DE=DEscore,nperm = 1000,r = 0.9,p = 10^-10)
The function "DrugSimscore" is used in calculating the drug functional similarity score.
DrugSimscore(DE,nperm = 0)DrugSimscore(DE,nperm = 0)
DE |
A matrix with one column of zscore. |
nperm |
Number of random permutations (default: 0). |
A dataframe with four columns those are drug1, drug2, drug1 name, drug2 name, functional similarity score and FDR.
# Obtain the example data GEP<-Gettest("GEP") label<-Gettest("label") # Run the function DEscore<-CalDEscore(GEP,label) # Run the function drug_drug<-DrugSimscore(DE=DEscore,nperm = 0)# Obtain the example data GEP<-Gettest("GEP") label<-Gettest("label") # Run the function DEscore<-CalDEscore(GEP,label) # Run the function drug_drug<-DrugSimscore(DE=DEscore,nperm = 0)
Get the example data
Gettest(exampleData)Gettest(exampleData)
exampleData |
A character,should be one of"Jaccard","commongenes","GO_MF","Drugs","Drugbankid_CID","drugname","GEP","label" |
data
An environment variable which includes some example data. Jaccard:A matrix of Jaccard score between drugs and GOMF. commongenes:A matrix consisting of genes shared by drug targets and GOMF. GO_MF:GO terms of molecular functions. Drugs:Drugs and corresponding targets. GEP:An example gene expression profile. label:A vector representing the label of the sample of GEP, where "1" is the disease sample and "0" is the normal sample. Drugbankid_CID:A dataframe including three columns which are drugbankid, ChembleID, and drugname.
myenvmyenv
An environment variable
The function "plotDruglink" is used to plot a bipartite network of drugs and shared molecular functions.
plotDruglink(drug1,drug2,i = 5,color_MF = "#43AAEF",color_drug = "#F7525B", layout_type = "circle")plotDruglink(drug1,drug2,i = 5,color_MF = "#43AAEF",color_drug = "#F7525B", layout_type = "circle")
drug1 |
The drugbank ID of drug1. |
drug2 |
The drugbank ID of drug2. |
i |
Specifies the number of outputs molecular functions, which is 5 by default. |
color_MF |
Defines the color of MF nodes in the network. |
color_drug |
Defines the color of drug nodes in the network. |
layout_type |
layout_type used to set the appropriate arrangement, there is an option to choose from "circle","dh",and "sugiyama". |
A bipartite network of drugs and shared molecular functions.
# Set drug1 drug1<-"DB02721" # Set drug2 drug2<-"DB01213" # Run the function library(igraph) plotDruglink(drug1,drug2,i = 5)# Set drug1 drug1<-"DB02721" # Set drug2 drug2<-"DB01213" # Run the function library(igraph) plotDruglink(drug1,drug2,i = 5)
The function "plotDrugstructure" can plot the chemical structure of a drug.
plotDrugstructure(drugid = "")plotDrugstructure(drugid = "")
drugid |
A drugbank ID. |
A chemical structure of specific drug
# Load depend package library(ChemmineR) library(rvest) # Obtain molecular formula and visualize it. plotDrugstructure(drugid ="DB00780")# Load depend package library(ChemmineR) library(rvest) # Obtain molecular formula and visualize it. plotDrugstructure(drugid ="DB00780")
The function "plotTargetheatmap" is used to plot a heat map of drug targets expression.
plotTargetheatmap(drugid,ExpData,label,significance=FALSE, cluster.rows=FALSE,cluster.cols=FALSE,bk=c(-2.4,2.3),show.rownames=TRUE, show.colnames=FALSE,ann_colors=c("#FFAA2C","#2CBADA"),col=c("#2A95FF","#FF1C1C"))plotTargetheatmap(drugid,ExpData,label,significance=FALSE, cluster.rows=FALSE,cluster.cols=FALSE,bk=c(-2.4,2.3),show.rownames=TRUE, show.colnames=FALSE,ann_colors=c("#FFAA2C","#2CBADA"),col=c("#2A95FF","#FF1C1C"))
drugid |
The drugbank ID of a drug. |
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. |
significance |
This parameter controls whether the p-value of differential expression is displayed. |
cluster.rows |
Logical value that represents whether row clustering is used. |
cluster.cols |
Logical value that represents whether col clustering is used. |
bk |
This parameter adjusts the range of values displayed by the color bar. |
show.rownames |
This parameter controls whether row names are displayed. |
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. |
A heat map of drug targets expression.
# Obtain the example data GEP<-Gettest("GEP") label<-Gettest("label") # Run the function plotTargetheatmap("DB00780",GEP,label)# Obtain the example data GEP<-Gettest("GEP") label<-Gettest("label") # Run the function plotTargetheatmap("DB00780",GEP,label)