PolygonRrClusterG: Construct a network layout. Calculate the layout according to...
In taowenmicro/ggClusterNet:

PolygonRrClusterG

R Documentation

Construct a network layout. Calculate the layout according to grouping and random distribution

Description

Construct a network layout. Calculate the layout according to grouping and random distribution

Usage

PolygonRrClusterG(cor = cor, nodeGroup = netClu, zoom = 1, zoom2 = 1, bio = F)

PolygonRrClusterG(cor = cor, nodeGroup = netClu, zoom = 1, zoom2 = 1, bio = F)

Arguments

`cor`	Correlation matrix
`nodeGroup`	Classification information of network nodes
`zoom`	Set the distance between modules
`zoom2`	Scaling module radius size

Value

result2 Which contains 2 lists.Result2[[1]], consists of OTU and its corresponding coordinates. result2[[2]], consists of the network center coordinates of each group

Author(s)

Contact: Tao Wen 2018203048@njau.edu.cn Jun Yuan junyuan@njau.edu.cn Penghao Xie 2019103106@njau.edu.cn

References

Yuan J, Zhao J, Wen T, Zhao M, Li R, Goossens P, Huang Q, Bai Y, Vivanco JM, Kowalchuk GA, Berendsen RL, Shen Q Root exudates drive the soil-borne legacy of aboveground pathogen infection Microbiome 2018,DOI: doi: 10.1186/s40168-018-0537-x

Examples

data
data(ps)
result = corMicro (ps = ps,N = 100,r.threshold=0.8,p.threshold=0.05,method = "pearson")
#Extract correlation matrix
cor = result[[1]]
# building the node group
ps_net = result[[3]]
vegan_tax <-  function(physeq){
tax <-  tax_table(physeq)

return(as(tax,"matrix"))
}
tax_table = as.data.frame(vegan_tax(ps_net))
group = as.data.frame(tax_table)
group$ID = row.names(group)
netClu = data.frame(ID = row.names(group),group = group$Phylum)
netClu$group = as.factor(netClu$group)
result2 = PolygonRrClusterG (cor = cor,nodeGroup =netClu )
node = result2[[1]]


data
data(ps)
result = corMicro (ps = ps,N = 0.02,r.threshold=0.8,p.threshold=0.05,method = "pearson")
#Extract correlation matrix
cor = result[[1]]
# building the node group
ps_net = result[[3]]
vegan_tax <-  function(physeq){
tax <-  tax_table(physeq)

return(as(tax,"matrix"))
}
tax_table = as.data.frame(vegan_tax(ps_net))
group = as.data.frame(tax_table)
group$ID = row.names(group)
netClu = data.frame(ID = row.names(group),group = group$Phylum)
netClu$group = as.factor(netClu$group)
result2 = PolygonRrClusterG (cor = cor,nodeGroup =netClu )
node = result2[[1]]

taowenmicro/ggClusterNet documentation built on March 29, 2024, 1:32 a.m.