mappingPathwaysClusters: Outputs a table with pathways and their respective clusters

In pouryany/PanomiR: Detection of miRNAs that regulate interacting groups of pathways

Outputs a table with pathways and their respective clusters

Description

Outputs a table with pathways and their respective clusters

Usage

mappingPathwaysClusters(
  pcxn,
  dePathways,
  clusteringFunction = NULL,
  edgeFDR = 0.05,
  correlationCutOff = 0.316,
  pathwayFDR = 0.05,
  topPathways = 200,
  plotOut = TRUE,
  subplot = TRUE,
  topClusters = 2,
  prefix = "",
  outDir = ".",
  saveNameCSV = NULL,
  weighted = FALSE
)

Arguments

pcxn	pathways network (edge list of pathways)
dePathways	differential expressed pathways, obtained from *DifferentialPathwayAnalysis*
clusteringFunction	clustering algorithm
edgeFDR	FDR threshold for pathway-pathway adjusted p-values; filter edges with adjusted p-values less than given threshold
correlationCutOff	cut-off threshold for pathway-pathway correlation; filter pathways with correlation less than given threshold
pathwayFDR	FDR threshold for DE pathways adjusted p-values; filter pathways with adjusted p-values less than given threshold
topPathways	use only top x paths; if NULL, use all paths
plotOut	if TRUE, store graph plot in Figures directory of plots
subplot	if TRUE, store individual clusters plots and connected plots in Figures directory of plots
topClusters	plot figures for top x clusters
prefix	add prefix to plots
outDir	output directory
saveNameCSV	if not NULL, saves output as csv using save name
weighted	True if you wish to include correlation weights in clustering

Value

a list where the first item is a table with each row containing a pathway and its respective cluster. The second item is an igraph object.

Examples

data("miniTestsPanomiR")

mappingPathwaysClusters(pcxn = miniTestsPanomiR$miniPCXN,
                         dePathways = miniTestsPanomiR$miniDEP,
                         topPathways = 200,
                         outDir=".",
                         plot = FALSE,
                         subplot = FALSE,
                         prefix='',
                         clusteringFunction = "cluster_louvain",
                         correlationCutOff = 0.1)

pouryany/PanomiR documentation built on Aug. 20, 2022, 11:17 p.m.