View source: R/parallelCoordinates.r
parallelCoordinates | R Documentation |
Represents expression levels through gene and/or condition profiles in a bicluster as lines.
parallelCoordinates(x, bicResult, number, plotBoth = FALSE, plotcol = TRUE,
compare = TRUE, info = F, bothlab = c("Rows", "Columns"), order = FALSE,
order2 = 0,ylab = "Value" , col=1,...)
x |
The data matrix of the bicluster to be drawn |
bicResult |
BiclustResult object with a bicluster result set |
number |
Bicluster to be drawn from the result set 'bicResult' |
plotBoth |
If 'TRUE', Parallel Coordinates of rows (Genes) and columns (Conditions) were drawn one below the other. |
plotcol |
If 'TRUE', columns profiles are drawn, so each line represents one of the columns in the bicluster. Otherwise, row profiles are drawn. Default 'TRUE' |
compare |
If 'TRUE', values of the complete data matrix are considered and drawn as shaded lines. Default 'TRUE' |
info |
If 'TRUE', a prepared Title is drawn |
bothlab |
Names of the x Axis if PlotBoth |
order |
Rows and/or Columns are in increasing order. |
order2 |
Which ordering. |
ylab |
ylab |
col |
col |
... |
Plot Parameters |
Rodrigo Santamaria, Martin Sill and Sebastian Kaiser sebastian.kaiser@stat.uni-muenchen.de
drawHeatmap
for alternative representation of biclusters and bubbleplot
for simultaneous representation of biclusters.
#Random 100x50 matrix with a single, up-regulated 10x10 bicluster
s2=matrix(rnorm(5000),100,50)
s2[11:20,11:20]=rnorm(100,3,0.3)
set.seed(1)
bics <- biclust(s2,BCPlaid(), back.fit = 2, shuffle = 3, fit.model = ~m + a + b,
iter.startup = 5, iter.layer = 30, verbose = TRUE)
parallelCoordinates(x=s2,bicResult=bics,number=1, plotBoth=TRUE,
plotcol=TRUE, compare=TRUE, info=TRUE,bothlab=c("Genes Bicluster
1","Conditions Bicluster 1"), order =TRUE)
parallelCoordinates(x=s2,bicResult=bics,number=1, plotBoth=FALSE, plotcol=TRUE,
compare=FALSE, info=TRUE)
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