getDownstreamNetwork: getDownstreamNetwork - Create a network
In juanbot/CoExpNets: Co-expression network management based on WGCNA + k-means

getDownstreamNetwork - Create a network

getDownstreamNetwork(
  tissue = "mytissue",
  n.iterations = 50,
  min.exchanged.genes = 20,
  expr.data,
  beta = -1,
  job.path = "~/tmp/",
  min.cluster.size = 30,
  net.type = "signed",
  debug = F,
  blockTOM = F,
  save.tom = F,
  save.plots = F,
  excludeGrey = FALSE,
  fullAnnotation = T,
  silent = T
)

`tissue`	A label to use to refer to the results in files and downstream results
`n.iterations`	Number of iterations in the k-means algorithm to refine the clustering process
`expr.data`	A data frame with expression data, ready to get into WGCNA. Columns are genes and rows are samples. Column names will be used as gene names in the analysis product
`beta`	The smoothing parameter of the WGCNA pipeline. If -1, then the method will suggest one automatically by looking at the R2 between gene connectivity and Scale Free Topology features
`job.path`	This method will generate a number of files. It needs a folder to write results
`min.cluster.size`	Minimum number of genes for a group to be considered as cluster for the tree cutting algorithm to convert from a dendogram to a cluster.
`net.type`	Whether a signed ("signed") or unsigned ("unsigned") network type will be created
`debug`	Set this to true if you want a quick run of the method to test how it works with a small amount of your genes
`excludeGrey`	If WGCNA detects grey genes, set it to TRUE if you want them removed from the network before applying k-means