Make a heatmap of gene expression from multiple datasets.
Usage
plotExpressionHeatmap(
fitResult,
lambda,
ematMerged,
sampleMetadata,
annoLevels,
annoColors = NA,
clusterTogether = FALSE,
geneIdOrder = NA,
className = "class",
classLevels = NA,
org = "org.Hs.eg",
maxVal = 3,
...
)
Arguments
- fitResult
glmnet
object.- lambda
value of lambda to use in
fitResult
.- ematMerged
matrix of gene expression for genes by samples.
- sampleMetadata
data.frame of sample metadata.
- annoLevels
Named list used to make the
annotation
argument passed topheatmap::pheatmap()
. Each name must correspond to a column name insampleMetadata
, and each item in the list must be a vector of values found in that particular column.- annoColors
Passed to
annotation_colors
argument ofpheatmap::pheatmap()
.- clusterTogether
logical indicating whether to cluster the samples from each dataset together or separately.
- geneIdOrder
Optional character array of Entrez Gene IDs specifying the order of genes. If
NA
(default), the order frommakeCoefDt()
is used.- className
column in sampleMetadata containing values of the response variable.
- classLevels
Order of classes for the column annotations.
- org
Name of package for mapping Entrez Gene IDs to gene symbols, passed to
data
argument ofannotate::lookUp()
.- maxVal
Maximum absolute value of scaled and centered gene expression, used to control dynamic range of color in the heatmap.
- ...
Additional arguments passed to
pheatmap::pheatmap()
.