formatPathways {netgsa} | R Documentation |
Format cytoscape nested networks
Description
Format cytoscape nested networks using preset NetGSA format
Usage
formatPathways(x, pways, graph_layout = NULL)
Arguments
x |
A NetGSA object returned from calling |
pways |
Character vector of pathways to format |
graph_layout |
(Optional) Layout to pass to plots. Must be a string for Cytoscape which will be passed to |
Details
Loads gene testing data into each pathway. Genes are tested using an F-test if there are 2 or more conditions or a two-sided one-class t-test against the null hypothesis of mean = 0 if there is only one condition. FDR corrected q-values are mapped to the color of the node. The scale ranges from 0 to 1 with red represents q-values of 0 and white representing q-values of 1. Loaded data includes: p-value from the F-test/t-test (pval), FDR corrected q-value (pFdr), test statistic from the F-test/t-test (teststat).
Custom formatting can be applied using the cytoscape GUI or the RCy3 pacakge.
Value
No return value, called for side effects
Author(s)
Michael Hellstern
References
Ma, J., Shojaie, A. & Michailidis, G. (2016) Network-based pathway enrichment analysis with incomplete network information. Bioinformatics 32(20):165–3174.
See Also
Examples
## Not run:
## load the data
data("breastcancer2012_subset")
## consider genes from just 2 pathways
genenames <- unique(c(pathways[["Adipocytokine signaling pathway"]],
pathways[["Adrenergic signaling in cardiomyocytes"]]))
sx <- x[match(rownames(x), genenames, nomatch = 0L) > 0L,]
db_edges <- obtainEdgeList(rownames(sx), databases = c("kegg", "reactome"))
adj_cluster <- prepareAdjMat(sx, group, databases = db_edges, cluster = TRUE)
out_cluster <- NetGSA(adj_cluster[["Adj"]], sx, group,
pathways_mat[c(1,2), rownames(sx)], lklMethod = "REHE", sampling = FALSE)
plot(out_cluster)
formatPathways(out_netgsa, "Adipocytokine signaling pathway")
## End(Not run)