Description Usage Arguments Details Value
View source: R/script_tissue_specific_efficacy_score.R
Given a set of gene targets, it builds the corresponding tissue-specific networks, the set of genes linking the targets to disease genes, a set of genes tightly connected to all targets.
1 2 3 4 5 6 7 8 9 10 11 12 | build.tissue.specific.networks(
tissue_scores,
disease_genes,
ppi_network,
directed_network = F,
tissue_expr_data,
top_targets = NULL,
rwr_restart = 0.75,
rwr_norm = "quantile",
rwr_cutoff = 0.001,
verbose = FALSE
)
|
tissue_scores |
a data.frame as the one compiled by |
disease_genes |
character vector containing the IDs of the genes related to a particular disease.
Gene IDs are expected to match with those provided in |
ppi_network |
a matrix or a data frame with at least two columns reporting the ppi connections (or edges). Each line corresponds to a direct interaction. Columns give the gene IDs of the two interacting proteins. |
directed_network |
logical indicating whether the PPI is directed. |
tissue_expr_data |
a numeric matrix or data frame indicating expression significances
in the form of Z-scores. Columns are tissues and rows are genes; colnames and rownames must be provided.
Gene IDs are expected to match with those provided in |
top_targets |
character vector indicating a list of ENTREZ id to be used for the slection of the shortest paths. |
rwr_restart |
the restart probability used for RWR. See |
rwr_norm |
the way to normalise the adjacency matrix of the input graph. See |
rwr_cutoff |
the cuoff value to select the most visited genes. |
verbose |
logical indicating whether the messages will be displayed or not in the screen. |
The top targets are used to re-build the shortest paths with the disease-relevant genes in tissue-specific networks. The shortest paths linkining a top target to disease genes are merged and the resulting set of nodes/genes are giving in output. Moreover, random walk with restart is utilized to identify a set of genes that is tightly connected to the targets.
a list of four objects:
- tsn: a list of tissue-specific networks;
- shp: a list of gene sets, each gene set indicates the genes connecting a target to all disease genes;
- tsn: a list of gene sets, each gene set represents the set of genese that are closely related to the set of targets;
- universe: the total number of genes in the tissue-specific networks.
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