plot_cor {clustifyr} | R Documentation

## Plot similarity measures on a tSNE or umap

### Description

Plot similarity measures on a tSNE or umap

### Usage

    plot_cor(
      cor_mat,
      metadata,
      data_to_plot = colnames(cor_mat),
      cluster_col = NULL,
      x = "UMAP_1",
      y = "UMAP_2",
      scale_legends = FALSE,
      ...
    )

### Arguments

`cor_mat` | input similarity matrix
`metadata` | input metadata with per cell tsne or umap coordinates and cluster ids
`data_to_plot` | colname of data to plot, defaults to all
`cluster_col` | colname of clustering data in metadata, defaults to rownames of the metadata if not supplied.
`x` | metadata column name with 1st axis dimension. defaults to "UMAP_1".
`y` | metadata column name with 2nd axis dimension. defaults to "UMAP_2".
`scale_legends` | if TRUE scale all legends to maximum values in entire correlation matrix. if FALSE scale legends to maximum for each plot. A two-element numeric vector can also be passed to supply custom values i.e. c(0, 1)
`...` | passed to plot_dims

### Value

list of ggplot objects, cells projected by dr, colored by cor values

### Examples

    res <- clustify(
        input = pbmc_matrix_small,
        metadata = pbmc_meta,
        ref_mat = cbmc_ref,
        query_genes = pbmc_vargenes,
        cluster_col = "classified"
    )

    plot_cor(
        cor_mat = res,
        metadata = pbmc_meta,
        data_to_plot = colnames(res)[1:2],
        cluster_col = "classified",
        x = "UMAP_1",
        y = "UMAP_2"
    )

[Package clustifyr version 1.0.0 Index]