| Type: | Package |
| Title: | Candidate Gene Prioritization for Non-Communicable Diseases Based on Functional Information |
| Version: | 1.0.1 |
| biocViews: | GraphAndNetwork, FunctionalGenomics, Genetics, Network |
| Description: | In gene sequencing methods, the topological features of protein-protein interaction (PPI) networks are often used, such as ToppNet https://toppgene.cchmc.org. In this study, a candidate gene prioritization method was proposed for non-communicable diseases considering disease risks transferred between genes in weighted disease PPI networks with weights for nodes and edges based on functional information. |
| Depends: | R (≥ 3.6.0) |
| License: | Artistic-2.0 |
| Encoding: | UTF-8 |
| LazyData: | true |
| RoxygenNote: | 7.0.2 |
| Suggests: | knitr, rmarkdown, testthat |
| VignetteBuilder: | knitr |
| Imports: | AnnotationDbi, org.Hs.eg.db |
| NeedsCompilation: | no |
| Packaged: | 2020-02-01 16:39:53 UTC; Administrator |
| Author: | Erqiang Hu [aut, cre] |
| Maintainer: | Erqiang Hu <13766876214@163.com> |
| Repository: | CRAN |
| Date/Publication: | 2020-02-01 17:00:02 UTC |
the vector of initial disease risk scores for all genes
Description
the vector of initial disease risk scores for all genes
Usage
R_0
Format
A vector of 45 number
Title deal with network
Description
Title deal with network
Usage
deal_net(net, dise_gene)
Arguments
net |
a network |
dise_gene |
a matrix with one column of genes |
Value
a matrix
Examples
deal_net(net,dise_gene)
a vector of disease related genes
Description
some genes
Usage
dise_gene
Format
A matrix with 79 rows and 1 column
weights of edges of a net
Description
the first two columns are a net, and third column is their weight
Usage
edge_weight
Format
A matrix with 25 rows and 3 columns
a one-to-many matrix of GO term and gene
Description
the first column is the gene symbol, the second column is the go terms
Usage
genes_mat
Format
A matrix with 45 rows and 3 columns
Details
the third column is the number of go terms
Title get the disease risk transition probability matrix
Description
Title get the disease risk transition probability matrix
Usage
get_Q(node_weight, net_disease_term)
Arguments
node_weight |
a matrix, genes and their weights |
net_disease_term |
GO terms for each pair of nodes in the network |
Value
a matrix
Title get the final genetic disease risk scores
Description
Title get the final genetic disease risk scores
Usage
get_R(node_weight, net_disease_term, bet, R_0, threshold = 10^(-9))
Arguments
node_weight |
a matrix, genes and their weights |
net_disease_term |
GO terms for each pair of nodes in the network |
bet |
a parameter to measure the importance of genes and interactions |
R_0 |
the vector of initial disease risk scores for all genes |
threshold |
a threshold for terminating iterations |
Value
a matrix
Examples
net_disease <- deal_net(net,dise_gene)
genes_mat <- get_gene_mat(net_disease)
node_weight <- get_node_weight(genes_mat)
net_disease_term <- get_net_disease_term(genes_mat,net_disease)
R_0<- get_R_0(dise_gene,node_weight,f=1)
result <- get_R(node_weight, net_disease_term, bet = 0.5, R_0 = R_0, threshold = 10^(-9))
Title get the vector of initial disease risk scores for all genes
Description
Title get the vector of initial disease risk scores for all genes
Usage
get_R_0(disease_gene, node_weight, f = 1)
Arguments
disease_gene |
a matrix of a column of genes |
node_weight |
a matrix, genes and their weights |
f |
an integer parameter to measure the significance of disease genes and candidate genes |
Value
a vector
Examples
get_R_0(dise_gene,node_weight,1)
Title
Description
Title
Usage
get_W(node1, node2)
Arguments
node1 |
a gene |
node2 |
a gene |
Value
a number
Title weight edge
Description
Title weight edge
Usage
get_edge_weight(net_disease_term, terms_mat)
Arguments
net_disease_term |
GO terms for each pair of nodes in the network |
terms_mat |
result of get_term_mat() |
Value
a matrix
Examples
get_edge_weight(net_disease_term,terms_mat)
Get a one-to-many matrix of gene and GO term
Description
Get a one-to-many matrix of gene and GO term
Usage
get_gene_mat(net_disease)
Arguments
net_disease |
a disease related network, matrix |
Value
a matrix
Examples
get_gene_mat(net_disease)
Title get neighbor of a node
Description
Title get neighbor of a node
Usage
get_neighbor(node, net)
Arguments
node |
a gene |
net |
a network |
Value
a vector of gene
Title Get the GO terms for each pair of nodes in the network
Description
Title Get the GO terms for each pair of nodes in the network
Usage
get_net_disease_term(genes_mat, net_disease)
Arguments
genes_mat |
a one-to-many matrix of GO term and gene |
net_disease |
a disease related network, matrix |
Value
a matrix
Examples
get_net_disease_term(genes_mat,net_disease)
Title weight node
Description
Title weight node
Usage
get_node_weight(genes_mat)
Arguments
genes_mat |
a one-to-many matrix of GO term and gene |
Value
a matrix
Examples
get_node_weight(genes_mat)
Get a one-to-many matrix of GO term and gene
Description
Get a one-to-many matrix of GO term and gene
Usage
get_term_mat(net_disease)
Arguments
net_disease |
a disease related network, matrix |
Value
a matrix
Examples
get_term_mat(net_disease)
a matrix, Human metabolic network
Description
a matrix, Human metabolic network
Usage
metabolic_net
Format
A matrix with 589,199 rows and 2 columns
a network of genes
Description
a network of genes
Usage
net
Format
A matrix with 2000 rows and 2 columns
a network of disease related genes
Description
a network of disease related genes
Usage
net_disease
Format
A matrix with 26 rows and 2 columns
GO terms for each pair of nodes in the network
Description
the first two columns is the network
Usage
net_disease_term
Format
A matrix with 25 rows and 4 columns
Details
the third column is the go terms,the fourth column is the number of go terms
the fourth column is the number of go terms
a matrix, genes and their weights
Description
a matrix, genes and their weights
Usage
node_weight
Format
A matrix with 45 rows and 2 columns
a matrix, GO terms and GO genes
Description
a one-to-many matrix of GO term and gene
Usage
terms_mat
Format
A matrix with 1172 rows and 3 columns