A correlogram or correlation matrix allows to analyse the relationship between each pair of numeric variables of a matrix.
{ "x" : { "Factor1" : ["Lev : 1","Lev : 2","Lev : 3","Lev : 1","Lev : 2","Lev : 3"], "Factor2" : ["Lev : A","Lev : B","Lev : A","Lev : B","Lev : A","Lev : B"], "Factor3" : ["Lev : X","Lev : X","Lev : Y","Lev : Y","Lev : Z","Lev : Z"], "Factor4" : [5,10,15,20,25,30], "Factor5" : [8,16,24,32,40,48], "Factor6" : [10,20,30,40,50,60] }, "y" : { "data" : [ [5,10,25,40,45,50], [95,80,75,70,55,40], [25,30,45,60,65,70], [55,40,35,30,15,1] ], "desc" : ["Magnitude1","Magnitude2"], "smps" : ["S1","S2","S3","S4","S5","S6"], "vars" : ["V1","V2","V3","V4"] }, "z" : { "Annt1" : ["Desc : 1","Desc : 2","Desc : 3","Desc : 4"], "Annt2" : ["Desc : A","Desc : B","Desc : A","Desc : B"], "Annt3" : ["Desc : X","Desc : X","Desc : Y","Desc : Y"], "Annt4" : [5,10,15,20], "Annt5" : [8,16,24,32], "Annt6" : [10,20,30,40] } }
{ "correlationAxis" : "samples", "graphType" : "Correlation", "showTransition" : "false", "title" : "Correlation Plot", "yAxisTitle" : "Correlation Title" }
library(canvasXpress) y=read.table("https://www.canvasxpress.org/data/cX-generic-dat.txt", header=TRUE, sep="\t", quote="", row.names=1, fill=TRUE, check.names=FALSE, stringsAsFactors=FALSE) x=read.table("https://www.canvasxpress.org/data/cX-generic-smp.txt", header=TRUE, sep="\t", quote="", row.names=1, fill=TRUE, check.names=FALSE, stringsAsFactors=FALSE) z=read.table("https://www.canvasxpress.org/data/cX-generic-var.txt", header=TRUE, sep="\t", quote="", row.names=1, fill=TRUE, check.names=FALSE, stringsAsFactors=FALSE) canvasXpress( data=y, smpAnnot=x, varAnnot=z, correlationAxis="samples", graphType="Correlation", showTransition=FALSE, title="Correlation Plot", yAxisTitle="Correlation Title" )
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