Title: Poly-Pharmacology Toolkit for Traditional Chinese Medicine Research
Version: 1.0.3
Description: Toolkit for Poly-pharmacology Research of Traditional Chinese Medicine. Based on the biological descriptors and drug-disease interaction networks, it can analyze the potential poly-pharmacological mechanisms of Traditional Chinese Medicine and be used for drug-repositioning in Traditional Chinese Medicine.
License: GPL (≥ 3)
URL: https://github.com/YuanlongHu/immcp
BugReports: https://github.com/YuanlongHu/immcp/issues
Depends: igraph, R (≥ 4.0.0)
Imports: clusterProfiler, DOSE, dplyr, methods, magrittr, Matrix, openxlsx, org.Hs.eg.db, pbapply, proxyC, purrr, rlang (≥ 1.0.2), stats, utils, visNetwork (≥ 0.3.1), arules, ggplot2, ggheatmap, factoextra
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
Encoding: UTF-8
RoxygenNote: 7.1.2
LazyData: true
NeedsCompilation: no
Packaged: 2022-05-12 05:24:26 UTC; DELL
Author: Yuanlong Hu ORCID iD [aut, cre]
Maintainer: Yuanlong Hu <huyuanlong1996@163.com>
Repository: CRAN
Date/Publication: 2022-05-12 05:50:02 UTC

Class BasicData This class represents the basic input data.

Description

Class BasicData This class represents the basic input data.

Slots

drugnet

A directed graph

vertices

Vertices of drug graph.

diseasenet

Disease network.

biomarker

Disease-related gene.

Author(s)

Yuanlong Hu

Class BioDescr This class represents the biological descriptor data.

Description

Class BioDescr This class represents the biological descriptor data.

Slots

drug_geneset

from drug to geneset.

geneset_gene

from geneset to gene for each drug.

anno

Geneset ID and description.

Author(s)

Yuanlong Hu

CreateBasicData

Description

Create BasicData Object

Usage

CreateBasicData(..., diseasenet = NULL, biomarker = NULL)

Arguments

...

Drug graph from PrepareData.

diseasenet

A graph of Disease-related gene from PrepareData.

biomarker

Character vector, the vector of Disease-related gene.

Value

A BasicData object.

Author(s)

Yuanlong Hu

Examples

data(drugdemo)
drug_herb <- PrepareData(drugdemo$drug_herb, from = "drug", to="herb")
herb_compound <- PrepareData(drugdemo$herb_compound, from = "herb", to="compound")
compound_target <- PrepareData(drugdemo$compound_target, from = "compound", to="target")
disease <- PrepareData(drugdemo$disease, diseaseID = "disease",from = "target", to="target")
BasicData <- CreateBasicData(drug_herb, herb_compound, compound_target, diseasenet = disease)

CreateDisDrugNet

Description

Create Disease-Drug Network

Usage

CreateDisDrugNet(BasicData, drug, disease)

Arguments

BasicData

BasicData object.

drug

Character vector, the drug.

disease

Character vector, the disease.

Value

A igraph object.

Author(s)

Yuanlong Hu

Examples

data(drugdemo)
drug_herb <- PrepareData(drugdemo$drug_herb, from = "drug", to="herb")
herb_compound <- PrepareData(drugdemo$herb_compound, from = "herb", to="compound")
compound_target <- PrepareData(drugdemo$compound_target, from = "compound", to="target")
disease <- PrepareData(drugdemo$disease, diseaseID = "disease",from = "target", to="target")
BasicData <- CreateBasicData(drug_herb, herb_compound, compound_target, diseasenet = disease)
DisDrugNet <- CreateDisDrugNet(BasicData, drug = "Drug1", disease = "disease")

Class HerbResult This class represents the biological descriptor data.

Description

Class HerbResult This class represents the biological descriptor data.

Slots

Drug_Herb

Data frame, Drug-herb relationship.

Herb_Herb

Herb-herb association Rule Graph, it is a directed graph.

Author(s)

Yuanlong Hu

PrepareData

Description

Prepare input format.

Usage

PrepareData(..., from, to, diseaseID, format = "single", sep)

Arguments

...

data frame, containing interaction information.

from

A charactor vector, containing "drug", "herb", "compound", or "target".

to

A character vector, containing "drug", "herb", "compound", or "target".

diseaseID

Charactor vector, diseaseID

format

one of "single" or "basket".

sep

Separator.

Value

A igraph object.

Author(s)

Yuanlong Hu

Examples

data(drugdemo)
drug_herb <- PrepareData(drugdemo$drug_herb, from = "drug", to="herb")
herb_compound <- PrepareData(drugdemo$herb_compound, from = "herb", to="compound")
compound_target <- PrepareData(drugdemo$compound_target, from = "compound", to="target")
disease <- PrepareData(drugdemo$disease, diseaseID = "disease",from = "target", to="target")

diff_network_char

Description

Calculate the difference of network characters in two network

Usage

diff_network_char(graph1, graph2, output_all = FALSE)

Arguments

graph1

A igraph object.

graph2

A igraph object.

output_all

FALSE

Value

A number vector.

Author(s)

Yuanlong Hu

Datasets Demo dataset

Description

Datasets Demo dataset

enrich_f

Description

Enrich Analysis

Usage

enrich_f(
  target_character,
  geneset = c("kegg", "mkegg", "go", "wp"),
  arguments = list(minGSSize = 5, maxGSSize = 500, pvalue = 0.05, qvalue = 0.1),
  out_dataframe = TRUE,
  to_ENTREZID = TRUE
)

Arguments

target_character

Charactor vector of gene.

geneset

Charactor vector, one of "kegg"(KEGG), "mkegg"(KEGG Module), "go"(GO-BP), and "wp"(WikiPathways); a data frame and list.

arguments

A list of the arguments of clusterProfiler, including minGSSize, maxGSSize, pvalue, and qvalue.

out_dataframe

Logical, whether to output data frame,defaults to FALSE.

to_ENTREZID

Logical, whether to translate to ENTREZID from SYMBOL, defaults to TRUE.

Value

data frame

Author(s)

Yuanlong Hu

Export an xlsx file to Cytoscape

Description

Export an xlsx file to Cytoscape.

Usage

exportCytoscape(graph, file)

Arguments

graph

igraph object.

file

file

Value

A workbook object

Author(s)

Yuanlong Hu

Extract Biological descriptor

Description

Extract Biological descriptor

Usage

extr_biodescr(
  BasicData,
  geneset = c("kegg", "mkegg", "go", "wp"),
  arguments = list(minGSSize = 5, maxGSSize = 500, pvalue = 0.05, qvalue = 0.1),
  ref_type = "drug",
  ref = NULL,
  to_ENTREZID = TRUE
)

Arguments

BasicData

BasicData object.

geneset

Charactor vector, one of "kegg"(KEGG), "mkegg"(KEGG Module), "go"(GO-BP), and "wp"(WikiPathways); a data frame and list.

arguments

A list of the arguments of clusterProfiler, including minGSSize, maxGSSize, pvalue, and qvalue.

ref_type

Charactor vector, one of "drug", "herb", "compound" or "target", defaults to "drug".

ref

Charactor vector, reference drug, herb, compound or target, defaults to NULL.

to_ENTREZID

Logical, whether to translate to ENTREZID from SYMBOL, defaults to TRUE.

Value

A BioDescr object.

Author(s)

Yuanlong Hu

Extract Biological descriptor

Description

Extract Biological descriptor

Usage

## S4 method for signature 'BasicData'
extr_biodescr(
  BasicData,
  geneset = c("kegg", "mkegg", "go", "wp"),
  arguments = list(minGSSize = 5, maxGSSize = 500, pvalue = 0.05, qvalue = 0.1),
  ref_type = "drug",
  ref = NULL,
  to_ENTREZID = TRUE
)

Arguments

BasicData

BasicData object.

geneset

Charactor vector, one of "kegg"(KEGG), "mkegg"(KEGG Module), "go"(GO-BP), and "wp"(WikiPathways); a data frame and list.

arguments

A list of the arguments of clusterProfiler, including minGSSize, maxGSSize, pvalue, and qvalue.

ref_type

Charactor vector, one of "drug", "herb", "compound" or "target", defaults to "drug".

ref

Charactor vector, reference drug, herb, compound or target, defaults to NULL.

to_ENTREZID

Logical, whether to translate to ENTREZID from SYMBOL, defaults to TRUE.

Value

A BioDescr object.

Examples

## Not run: 
data(drugdemo)
drug_herb <- PrepareData(drugdemo$drug_herb, from = "drug", to="herb")
herb_compound <- PrepareData(drugdemo$herb_compound, from = "herb", to="compound")
compound_target <- PrepareData(drugdemo$compound_target, from = "compound", to="target")
disease <- PrepareData(drugdemo$disease, diseaseID = "disease",from = "target", to="target")
BasicData <- CreateBasicData(drug_herb, herb_compound, compound_target, diseasenet = disease)
biodescr <- extr_biodescr(BasicData, geneset= "kegg")

## End(Not run)

natural_connectivity

Description

Calculate the natural connectivity

Usage

natural_connectivity(graph)

Arguments

graph

A igraph object.

Value

A numeric vector.

Author(s)

Yuanlong Hu

network_char

Description

Calculate the network characters

Usage

network_char(graph, total_network = FALSE)

Arguments

graph

The graph.

total_network

Calculate for total network or each nodes.

Value

A number vector or data frame.

Author(s)

Yuanlong Hu

network_node_ks

Description

Kolmogorov-Smirnov tests for node characters between networks

Usage

network_node_ks(graph1, graph2, replicate = 1000)

Arguments

graph1

A igraph object.

graph2

A igraph object.

replicate

Number vector, the number of conduct bootstrapping sampling replications.

Value

A data frame

Author(s)

Yuanlong Hu

Plot Biological descriptor

Description

Plot Biological descriptor

Usage

plot_BioDescr(
  BioDescr,
  type = "heatmap",
  cluster_k = 2,
  colors = c("#2E9FDF", "#E7B800")
)

Arguments

BioDescr

BioDescr object.

type

one of "heatmap" and "clusterplot".

cluster_k

Number vector, number of cluster.

colors

vector of colors.

Value

Returns NULL, invisibly.

Plot Disease-Drug Network

Description

Plot Disease-Drug Network

Usage

plot_graph(
  graph,
  drug,
  disease,
  Isolated = TRUE,
  vis = "visNetwork",
  color = c(drug = "#cca4e3", herb = "#ff461f", compound = "#ffc773", target =
    "#70f3ff"),
  width = 1,
  size = 20,
  ...
)

## S4 method for signature 'BasicData'
plot_graph(
  graph,
  drug,
  disease,
  Isolated = TRUE,
  vis = "visNetwork",
  color = c(drug = "#cca4e3", herb = "#ff461f", compound = "#ffc773", target =
    "#70f3ff"),
  width = 1,
  size = 20,
  ...
)

## S4 method for signature 'igraph'
plot_graph(
  graph,
  drug,
  disease,
  Isolated = TRUE,
  vis = "visNetwork",
  color = c(drug = "#cca4e3", herb = "#ff461f", compound = "#ffc773", target =
    "#70f3ff"),
  width = 1,
  size = 20,
  ...
)

## S4 method for signature 'HerbResult'
plot_graph(
  graph,
  drug,
  disease,
  Isolated = TRUE,
  vis = "visNetwork",
  color = c(drug = "#cca4e3", herb = "#ff461f", compound = "#ffc773", target =
    "#70f3ff"),
  width = 1,
  size = 20,
  ...
)

Arguments

graph

graph.

drug

drug.

disease

disease.

Isolated

Whether to delect Isolated nodes.

vis

one of "igraph", "visNetwork" and "shiny".

color

Nodes Color

width

Edges width

size

Nodes size

...

Arguments

Value

Returns NULL, invisibly.

Author(s)

Yuanlong Hu

write_gmt

Description

parse gmt file to a data.frame

Usage

read_gmt(gmtfile, out_dataframe = TRUE)

Arguments

gmtfile

A GMT file name or URL containing gene sets.

out_dataframe

TRUE or FALSE

Value

data.frame, list

Author(s)

Yuanlong Hu

score_network

Description

Calculating differences in disease network characteristics before and after removal of drug targets

Usage

score_network(BasicData, n = 1000)

Arguments

BasicData

A BasicData object.

n

Number vector, the number of times random permutation sampling, default to 1000.

Value

A list.

Author(s)

Yuanlong Hu

Examples

data(drugdemo)
drug_herb <- PrepareData(drugdemo$drug_herb, from = "drug", to="herb")
herb_compound <- PrepareData(drugdemo$herb_compound, from = "herb", to="compound")
compound_target <- PrepareData(drugdemo$compound_target, from = "compound", to="target")
disease <- PrepareData(drugdemo$disease, diseaseID = "disease",from = "target", to="target")
BasicData <- CreateBasicData(drug_herb, herb_compound, compound_target, diseasenet = disease)
res <- score_network(BasicData, n = 100)

Mining herb-herb associations with Apriori

Description

Mine herb-herb association rules of prescription using the Apriori algorithm.

Usage

score_rule(BasicData, drug = NULL, support = 0.1, confidence = 0.8)

Arguments

BasicData

BasicData object.

drug

Charactor vector of drug names to analyze, default to NULL.

support

A numeric value for the minimal support of an item set, default to 0.1.

confidence

A numeric value for the minimal confidence of an item set, default to 0.8.

Value

A HerbResult object.

Author(s)

Yuanlong Hu

Examples

## Not run: 
data(drugdemo)
drug_herb <- PrepareData(drugdemo$drug_herb, from = "drug", to="herb")
herb_compound <- PrepareData(drugdemo$herb_compound, from = "herb", to="compound")
compound_target <- PrepareData(drugdemo$compound_target, from = "compound", to="target")
disease <- PrepareData(drugdemo$disease, diseaseID = "disease",from = "target", to="target")
BasicData <- CreateBasicData(drug_herb, herb_compound, compound_target, diseasenet = disease)
res <- score_rule(BasicData, support = 0.1,confidence = 0.8)

## End(Not run)

Calculating similarity between drug and disease

Description

Calculating drug-disease similarity based on biological descriptors

Usage

score_sim(BioDescr, method = "jaccard", n = 1000)

Arguments

BioDescr

BioDescr object.

method

method to compute similarity, default "jaccard". See proxyC::simil.

n

number.

Value

A list.

Author(s)

Yuanlong Hu

Examples

## Not run: 
data(drugdemo)
drug_herb <- PrepareData(drugdemo$drug_herb, from = "drug", to="herb")
herb_compound <- PrepareData(drugdemo$herb_compound, from = "herb", to="compound")
compound_target <- PrepareData(drugdemo$compound_target, from = "compound", to="target")
disease <- PrepareData(drugdemo$disease, diseaseID = "disease",from = "target", to="target")
BasicData <- CreateBasicData(drug_herb, herb_compound, compound_target, diseasenet = disease)
biodescr <- extr_biodescr(BasicData, geneset= "kegg")
res <- score_sim(biodescr, method="jaccard", n=1000)

## End(Not run)

to_biodescr

Description

Convert BioDescr object to a list of adjacency matrix

Usage

to_biodescr(BioDescr)

Arguments

BioDescr

A BioDescr object.

Value

A list.

Author(s)

Yuanlong Hu

Examples

## Not run: 
  to_biodescr(BioDescr)

## End(Not run)

to_df

Description

Convert list to data.frame

Usage

to_df(list)

Arguments

list

A list containing gene sets.

Value

A data frame.

Author(s)

Yuanlong Hu

Examples

## Not run: 
  to_df(list)

## End(Not run)

to_list

Description

Create a new list from a data.frame of drug target and disease biomarker as input

Usage

to_list(dataframe, input = "single", sep = ", ")

Arguments

dataframe

a data frame of 2 column with term/drug and gene

input

one of the single or basket

sep

When 'input' is 'basket'.

Value

list

Author(s)

Yuanlong Hu

Examples

## Not run: 
  to_list(dataframe)

## End(Not run)

write_gmt

Description

prints data frame to a gmt file

Usage

write_gmt(geneset, gmt_file)

Arguments

geneset

A data.frame of 2 column with term/drug and gene.

gmt_file

A character of gmt file name.

Value

gmt file

Author(s)

Yuanlong Hu