plotEmbedding {veloviz} | R Documentation

## Plot 2D embedding From scde/pagoda2/MUDAN

### Description

Plot 2D embedding From scde/pagoda2/MUDAN

### Usage

    plotEmbedding(
      emb,
      groups = NULL,
      colors = NULL,
      cex = 0.6,
      alpha = 0.4,
      gradientPalette = NULL,
      zlim = NULL,
      s = 1,
      v = 0.8,
      min.group.size = 1,
      show.legend = FALSE,
      mark.clusters = FALSE,
      mark.cluster.cex = 2,
      shuffle.colors = FALSE,
      legend.x = "topright",
      gradient.range.quantile = 0.95,
      verbose = TRUE,
      unclassified.cell.color = "gray70",
      group.level.colors = NULL,
      ...
    )

### Arguments

`emb` | dataframe with x and y coordinates
`groups` | factor annotations for rows on emb for visualizing cluster annotations
`colors` | color or numeric values for rows on emb for visualizing gene expression
`cex` | point size
`alpha` | point opacity
`gradientPalette` | palette for colors if numeric values provided
`zlim` | range for colors
`s` | saturation of rainbow for group colors
`v` | value of rainbow for group colors
`min.group.size` | minimum size of group in order for group to be colored
`show.legend` | whether to show legend
`mark.clusters` | whether to mark clusters with name of cluster
`mark.cluster.cex` | cluster marker point size
`shuffle.colors` | whether to shuffle group colors
`legend.x` | legend position ie. 'topright', 'topleft', 'bottomleft', 'bottomright'
`gradient.range.quantile` | quantile for mapping colors to gradient palette
`verbose` | verbosity
`unclassified.cell.color` | cells not included in groups will be labeled in this color
`group.level.colors` | set group level colors. Default uses rainbow.
`...` | Additional parameters to pass to BASE::plot

### Value

embedding plot

### Examples

    data(vel)
    curr <- vel$current
    proj <- vel$projected

    vv <- buildVeloviz(curr = curr, proj = proj, normalize.depth = TRUE,
    use.ods.genes = TRUE, alpha = 0.05, pca = TRUE, nPCs = 20, center = TRUE,
    scale = TRUE, k = 5, similarity.threshold = 0.25, distance.weight = 1,
    distance.threshold = 0.5, weighted = TRUE, verbose = FALSE)

    plotEmbedding(vv$fdg_coords)

[Package veloviz version 1.0.0 Index]