plotHeatmapPretrained: Plots rectangular AUROC heatmap, clustering train cell types...
In MetaNeighbor: Single cell replicability analysis

Plots rectangular AUROC heatmap, clustering train cell types (columns) by similarity, and ordering test cell types (rows) according to similarity to train cell types..

plotHeatmapPretrained(
  aurocs,
  alpha_col = 1,
  alpha_row = 10,
  cex = 1,
  margins = c(8, 8)
)

`aurocs`	A rectangular AUROC matrix as returned by MetaNeighborUS,
`alpha_col`	Parameter controling column clustering: a higher value of alpha_col gives more weight to extreme AUROC values (close to 1).
`alpha_row`	Parameter controling row ordering: a higher value of alpha_row gives more weight to extreme AUROC values (close to 1).
`cex`	Size factor for row and column labels.
`margins`	Size of margins (for row and column labels).

data(mn_data)
var_genes = variableGenes(dat = mn_data, exp_labels = mn_data$study_id)
celltype_NV = MetaNeighborUS(var_genes = var_genes,
                             dat = mn_data,
                             study_id = mn_data$study_id,
                             cell_type = mn_data$cell_type,
                             symmetric_output = FALSE)
keep_col = getStudyId(colnames(celltype_NV)) == "GSE71585"
keep_row = getStudyId(rownames(celltype_NV)) != "GSE71585"
plotHeatmapPretrained(celltype_NV[keep_row, keep_col])