Differential expression heatmap for mixscape
Draws a heatmap of single cell feature expression with cells ordered by their mixscape ko probabilities.
MixscapeHeatmap( object, ident.1 = NULL, ident.2 = NULL, balanced = TRUE, logfc.threshold = 0.25, assay = "RNA", max.genes = 100, test.use = "wilcox", max.cells.group = NULL, order.by.prob = TRUE, group.by = NULL, mixscape.class = "mixscape_class", prtb.type = "KO", fc.name = "avg_log2FC", pval.cutoff = 0.05, ... )
object |
An object |
ident.1 |
Identity class to define markers for; pass an object of class
|
ident.2 |
A second identity class for comparison; if |
balanced |
Plot an equal number of genes with both groups of cells. |
logfc.threshold |
Limit testing to genes which show, on average, at least X-fold difference (log-scale) between the two groups of cells. Default is 0.25 Increasing logfc.threshold speeds up the function, but can miss weaker signals. |
assay |
Assay to use in differential expression testing |
max.genes |
Total number of DE genes to plot. |
test.use |
Denotes which test to use. Available options are:
|
max.cells.group |
Number of cells per identity to plot. |
order.by.prob |
Order cells on heatmap based on their mixscape knockout probability from highest to lowest score. |
group.by |
Regroup cells into a different identity class prior to performing differential expression (see example) |
mixscape.class |
metadata column with mixscape classifications. |
prtb.type |
specify type of CRISPR perturbation expected for labeling mixscape classifications. Default is KO. |
fc.name |
Name of the fold change, average difference, or custom function column in the output data.frame. Default is avg_log2FC |
pval.cutoff |
P-value cut-off for selection of significantly DE genes. |
... |
Arguments passed to other methods and to specific DE methods |
A ggplot object.
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