I am trying to visualize the frequency of the different cells clusters on Seurat object clustered using SingleR. It is a naive question but am not sure what should I have in the Var. supposedly, it is the clusters in metadata but It keeps giving me the error "Error in .var_OR_get_meta_or_gene(var, object) : pred21@meta.data is not a metadata or gene nor equal in length to ncol('object')"

```dittoBarPlot( object = JHMV21, var = "pred21@meta.data")

and this is the singleR part

```JHMV21_counts <- GetAssayData(JHMV21, slot = 'counts') pred21 <- SingleR(test = JHMV21_counts, ref= ref, labels = ref$label.main)

```JHMV21$SingleR.labels <- pred21$labels[match(rownames(JHMV21@meta.data),rownames(pred21))] cluster4<- DimPlot(JHMV21, reduction = 'umap', group.by = 'SingleR.labels', label = TRUE, label.size =3)

It's a little hard to parse your code as it's not formatted properly, but I think I follow well enough.

dittoBarPlot expects you to give the name of a metadata column to var.

It looks like you have put your SingleR calls in a column called "SingleR.labels" with this code:

JHMV21$SingleR.labels <- pred21$labels[match(rownames(JHMV21@meta.data),rownames(pred21))]

You'll also need a secondary metadata to group.by, for which you could probably use 'orig.ident', but this will entirely depend on how you want to organize the data.

So try:

dittoBarPlot(
    JHMV21,
    var = 'SingleR.labels',
    group.by = 'orig.ident'
)

You may also wish to add scale = "count" to see numbers rather than percent.