base_Fastcornet2: fast way to create a network plot and edge/node data based on...

In shijianasdf/BasicBioinformaticsAnalysisFromZhongShan: Launch Usual Clinical tool for Kind Yield

Description

fast way to create a network plot and edge/node data based on a long data frame from a cormatrix.

Usage

Fastcornet2(data,
            source.col=NULL,target.col=NULL,value=NULL,
            color.group = list(),
            control.group = "control",
            ratio=0.8,
            legend=T,
            size = 15,
            linkColour=NULL,
            linkColour.type = list(
              name = "YlGn",
              select.lower = 1,
              select.upper = 9
            ),
            control.linkColour = "red",
            colourScale.type = NULL,
            nodeColour=list(),
            linkDistance = 300,
            linkWidth=6,
            opacity=1,
            arrows=F,
            zoom = T)

Arguments

data	a long data frame from a cormatrix
source.col,target.col,value	parameters as Make.cormatrix() in lucky package.
color.group	a named list of markers categery
control.group	the names of control group
ratio	select the most significant portion of correlations.it range 0 to 1.
legend	whether show legend in the netplot output
size	the index to enhance the degree difference among nodes.If you consider the size of nodes too small,try make size larger.
linkColour	link colour
linkColour.type	a list of parameters to RColorBrewer::brewer.pal
control.linkColour	the color of links to control group nodes.If NULL,use default colours,which is recommanded
colourScale.type	d3-scale-chromatic style object.1="d3.schemeCategory20",2="d3.schemeCategory20b",3="d3.schemeCategory20c",4="d3.schemeCategory10".Default is 1
nodeColour
linkDistance	link distance
linkWidth	the width of link.If it is not a numeric,the default "JS(function(d) return Math.sqrt(d.value); )" would be used.
opacity	numeric value of the proportion opaque you would like the graph elements to be
arrows	F.whether show direction between two nodes
zoom	logical value to enable (TRUE) or disable (FALSE) zooming

Details

linkColour.type make full use of RColorBrewer and would be a good color strategy provider.The parameters of linkColour.type is including: 1.names: One of "Blues","BuGn","BuPu","GnBu","Greens","Greys","Oranges","OrRd","PuBu","PuBuGn","PuRd","Purples","RdPu","Reds" ,"YlGn","YlGnBu","YlOrBr" and "YlOrRd"; 2.select.lower: the lower color order; 3.select.upper: the upper color order.

Value

a list contain a network plot information and edge/node data.

Author(s)

Weibin Huang<[e-mail]>

References

networkD3 package

See Also

networkD3::forceNetwork() lucky::Fastcornet

Examples

library(lucky)
data=state.x77;colnames(data)
## get MIC cormatrix
result1 <- FastMINE(data,
                    transposition = F,
                    method = "all.pairs",
                    control.markers="Income",
                    target.markers=NULL)

## long data frame network
data <- result1[["MINE.result"]][,1:3]
colnames(data) #[1] "X var"  "Y var" "MIC (strength)"
source.col="X var";target.col="Y var";value="MIC (strength)"

## parameters of Fastcornet2
color.group = list(
  love = c("Murder","Frost","Area","HS Grad"),
  hate = c("Life Exp","Illiteracy"),
  control = c("Population","Income"))
control.group = "control"
linkColour.type = list(
  name =  "Blues",
  select.lower = 1,
  select.upper = 3
)

# control.linkColour = "red"
control.linkColour = NULL
colourScale.type = NULL
nodeColour=list(
  love = mycolor[6],
  hate = mycolor[8],
  control = mycolor[35])

## Quick Start
nw2 <- Fastcornet2(data,
                   source.col,
                   target.col,
                   value,
                   color.group,
                   control.group,
                   ratio=0.8,
                   legend=T,
                   size = 15,
                   linkColour=NULL,
                   linkColour.type,
                   control.linkColour,
                   colourScale.type = NULL,
                   nodeColour);nw2$netplot

shijianasdf/BasicBioinformaticsAnalysisFromZhongShan documentation built on Jan. 3, 2020, 10:08 p.m.