plotIntegratedPatientNetwork {netDx} | R Documentation

## Visualize integrated patient similarity network based on selected features

### Description

Visualize integrated patient similarity network based on selected features

### Usage

    plotIntegratedPatientNetwork(dataList, groupList, makeNetFunc,
      setName = "predictor", prune_pctX = 0.05, prune_useTop = TRUE,
      aggFun = "MAX", calcShortestPath = FALSE, showStats = FALSE,
      outDir = tempdir(), numCores = 1L, nodeSize = 50L,
      edgeTransparency = 40L, nodeTransparency = 155L,
      plotCytoscape = FALSE, verbose = FALSE)

### Arguments

`dataList` | (MultiAssayExperiment) patient data & labels used as input
`groupList` | (list) features to use to create integrated patient network. Identical in structure to groupList in buildPredictor() method. This is a list of lists, where the outer list corresponds to assay (e.g. mRNA, clinical) and inner list to features to generate from that datatype.
`makeNetFunc` | (function) function to create features
`setName` | (char) name to assign the network in Cytoscape
`prune_pctX` | (numeric between 0 and 1) fraction of most/least edges to keep when pruning the integrated PSN for visualization. Must be used in conjunction with useTop=TRUE/FALSE e.g. Setting pctX=0.2 and useTop=TRUE will keep 20% top edges
`prune_useTop` | (logical) when pruning integrated PSN for visualization, determines whether to keep strongest edges (useTop=TRUE) or weakest edges (useTop=FALSE)
`aggFun` | (char) function to aggregate edges from different PSN
`calcShortestPath` | (logical) if TRUE, computes weighted shortest path Unless you plan to analyse these separately from looking at the shortest path violin plots or integrated PSN in Cytoscape, probably good to set to FALSE.
`showStats` | (logical) if FALSE, suppresses shortest path-related stats, such as one-sided WMW test for testing shorter intra-class distances
`outDir` | (char) path to directory for intermediate files. Useful for debugging.
`numCores` | (integer) number of cores for parallel processing
`nodeSize` | (integer) size of nodes in Cytoscape
`edgeTransparency` | (integer) Edge transparency. Value between 0 and 255, with higher numbers leading to more opacity.
`nodeTransparency` | (integer) Node transparency. Value between 0 and 255, with higher numbers leading to more opacity.
`plotCytoscape` | (logical) If TRUE, plots network in Cytoscape. Requires Cytoscape software to be installed and running on the computer when the function call is being made.
`verbose` | (logical) print detailed messages

### Details

Generates a Cytoscape network where nodes are patients and edges are weighted by aggregate pairwise patient similarity. Integrated PSN plotting is intended to run after feature selection, which identifies the subset of input networks predictive for each class of interest. The method of generating the network is as follows: All networks feature-selected in either patient ategory are concatenated; where a network is feature-selected in both categories, it is included once. The similarity between two patients in the integrated network is the mean of corresponding pairwise similarities. Dissimilarity is defined as 1-similarity, and Dijkstra distances are computed on this resulting network. For visualization, only edges representing the top fraction of distances (strongest edge weights) are included.

### Value

(list) information about the integrated network similarity network 2) patientDistNetwork_pruned (matrix) the network plotted in Cytoscape. Also note that this is a dissimilarity network, so that more similar nodes have smaller edge weights 3) colLegend (data.frame): legend for the patient network plotted in Cytoscape. Columns are node labels (STATUS) and colours (colour) 6) outDir (char) value of outDir parameter

[Package netDx version 1.1.4 Index]