plotContrastHeatmap,ClusterExperiment-method {clusterExperiment} | R Documentation |
Plots a heatmap of the data, with the genes grouped based on the contrast for which they were significant.
## S4 method for signature 'ClusterExperiment' plotContrastHeatmap(object, signifTable, whichCluster = NULL, contrastColors = NULL, ...)
object |
ClusterExperiment object on which biomarkers were found |
signifTable |
A |
whichCluster |
if not NULL, indicates cluster used in making the
significance table. Used to match to names in |
contrastColors |
vector of colors to be given to contrasts. Should match
the name of the contrasts in the 'Contrast' column of |
... |
Arguments passed to |
If the column 'ContrastName' is given in signifTable
, these
names will be used to describe the contrast in the legend.
Within each contrast, the genes are sorted by log fold-change if the
column "logFC" is in the signifTable
data.frame
A heatmap is created. The output of plotHeatmap
is returned.
plotHeatmap
, makeBlankData
,
getBestFeatures
data(simData) cl <- clusterSingle(simData, subsample=FALSE, sequential=FALSE, mainClusterArgs=list(clusterFunction="pam", clusterArgs=list(k=8))) #Do all pairwise, only return significant, try different adjustments: pairsPerC <- getBestFeatures(cl, contrastType="Pairs", number=5, p.value=0.05, DEMethod="limma") plotContrastHeatmap(cl,pairsPerC)