These functions facilitate heatmap plotting of a specified set of genes. By
default, row- and column-wise hierarchical clustering is performed using the
Ward method, but this behavior can be overrided by setting cluster_rows or
cluster_cols to FALSE. When column clustering is disabled, the columns
are sorted by the interesting groups (interestingGroups) specified in the
bcbioRNASeq and then the sample names.
plotGeneHeatmap(object, ...) # S4 method for bcbioRNASeq plotGeneHeatmap(object, genes = NULL, title = NULL, color = inferno(256), legendColor = viridis) # S4 method for DESeqDataSet plotGeneHeatmap(object, genes = NULL, annotationCol = NULL, title = NULL, color = inferno(256), legendColor = viridis) # S4 method for DESeqTransform plotGeneHeatmap(object, genes = NULL, annotationCol = NULL, title = NULL, color = inferno(256), legendColor = viridis) # S4 method for matrix plotGeneHeatmap(object, genes = NULL, annotationCol = NULL, title = NULL, color = inferno(256), legendColor = viridis)
| object | Object. |
|---|---|
| ... | Additional arguments (for the S4 generic definition). |
| genes | Character vector of specific gene identifiers to plot. |
| title | Optional. Plot title. |
| color | Colors to use for plot. Defaults to |
| legendColor | Colors to use for legend labels. Defaults to |
| annotationCol | data.frame that specifies the annotations shown on the right side of the heatmap. Each row of this data.frame defines the features of the heatmap columns. |
Graphical output only.
Other Heatmaps: plotCorrelationHeatmap,
plotDEGHeatmap
# Genes as Ensembl identifiers genes <- counts(bcb)[1:20, ] %>% rownames() plotGeneHeatmap(bcb, genes = genes)#>#>#>#># Flip the plot and legend palettes plotGeneHeatmap( bcb, genes = genes, color = viridis(256), legendColor = inferno)#>#>#>#># Transcriptome heatmap# NOT RUN { plotGeneHeatmap(bcb) # }# Use default pheatmap color palette# NOT RUN { plotGeneHeatmap( bcb, color = NULL, legendColor = NULL) # }# DESeqDataSet# NOT RUN { plotGeneHeatmap(dds) # }# DESeqTransform# NOT RUN { plotGeneHeatmap(rld) # }