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

Description Usage Arguments Details Value Author(s) References See Also Examples

Description

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

Usage

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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<[email protected]>

References

networkD3 package

See Also

networkD3::forceNetwork() lucky::Fastcornet

Examples

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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.