subset.dnapath_list | R Documentation |
Subset function for 'dnapath_list' object.
## S3 method for class 'dnapath_list' subset(x, pathways = NULL, genes = NULL, ...)
x |
A 'dnapath_list' object from |
pathways |
A set of pathways to index on. This can be (1) a vector of
character strings, corresponding to
pathway names or regular expressions used to find pathways, (2) a vector of
indices to select pathways, (3) a vector of
negative indices indicating pathways to remove, or (4) a logical (boolean)
vector that is the same length of current number of pathways in |
genes |
A set of gene names to index on; exact matching is used. Only pathways containing these genes are retained. |
... |
Additional arguments are ignored. |
A subset of the differential network analysis results.
data(meso) # Obtain a pathway list for this short example: pathway_list <- get_reactome_pathways("human", overlap_limit = NULL, min_size = 13, max_size = 19) # Run the differential network analysis. results <- dnapath(x = meso$gene_expression, pathway_list = pathway_list, group_labels = meso$groups, n_perm = 5, seed = 0) summary(results) # Summary over all pathways in the pathway list. # Subset on pathways that contain "cell cycle" in its name. cell_cycle_pathways <- subset(results, pathways = "cell cycle") summary(cell_cycle_pathways) # Subset on pathways that contain the gene 1026 (Entrezgene ID). pathways_with_1026 <- subset(results, genes = "1026") summary(pathways_with_1026) # Multiple pathways and/or genes can also be specified. # Specifying both acts as an "OR" operation. For example, the following subset # will contain pathways containing the words "acetylation" or "methylation" # OR pathways that contain the genes "1108" or "11200". results_OR <- subset(results, pathways = c("acetylation", "methylation"), genes = c("1108", "11200")) summary(results_OR) # To subset on pathways that have both a specific pathway name AND # certain genes, call the subset function twice: once specifying the # `pathways` argument, then pass those results back into subset() with the # `genes` argument specified. For example: results_AND <- subset(results, pathways = c("acetylation", "methylation")) results_AND <- subset(results_AND, genes = c("1108", "11200")) summary(results_AND)
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