plotHeatmapPretrained {MetaNeighbor} | R Documentation

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

### Description

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

### Usage

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

### Arguments

`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).

### Examples

    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])

[Package MetaNeighbor version 1.10.0 Index]