sccore (version 0.1.2)

dotPlot: Dot plot adapted from Seurat:::DotPlot, see ?Seurat:::DotPlot for details

Description

Dot plot adapted from Seurat:::DotPlot, see ?Seurat:::DotPlot for details

Usage

dotPlot(
  markers,
  count.matrix,
  cell.groups,
  marker.colour = "black",
  cluster.colour = "black",
  xlab = "Marker",
  ylab = "Cluster",
  n.cores = 1,
  text.angle = 45,
  gene.order = NULL,
  cols = c("blue", "red"),
  col.min = -2.5,
  col.max = 2.5,
  dot.min = 0,
  dot.scale = 6,
  scale.by = "radius",
  scale.min = NA,
  scale.max = NA,
  verbose = TRUE,
  ...
)

Arguments

markers

Vector of gene markers to plot

count.matrix

Merged count matrix, cells in rows and genes in columns

cell.groups

Named factor containing cell groups (clusters) and cell names as names

marker.colour

Character or numeric vector (default="black")

cluster.colour

Character or numeric vector (default="black")

xlab

string X-axis title (default="Marker")

ylab

string Y-axis title (default="Cluster")

n.cores

integer Number of cores (default=1)

text.angle

numeric Angle of text displayed (default=45)

gene.order

Either factor of genes passed to dplyr::mutate(levels=gene.order), or a boolean. (default=NULL) If TRUE, gene.order is set to the unique markers. If FALSE, gene.order is set to NULL. If NULL, the argument is ignored.

cols

Colors to plot (default=c("blue", "red")). The name of a palette from 'RColorBrewer::brewer.pal.info', a pair of colors defining a gradient, or 3+ colors defining multiple gradients (if 'split.by' is set).

col.min

numeric Minimum scaled average expression threshold (default=-2.5). Everything smaller will be set to this.

col.max

numeric Maximum scaled average expression threshold (default=2.5). Everything larger will be set to this.

dot.min

numeric The fraction of cells at which to draw the smallest dot (default=0). All cell groups with less than this expressing the given gene will have no dot drawn.

dot.scale

numeric Scale the size of the points, similar to cex (default=6)

scale.by

string Scale the size of the points by 'size' or by 'radius' (default="radius")

scale.min

numeric Set lower limit for scaling, use NA for default (default=NA)

scale.max

numeric Set upper limit for scaling, use NA for default (default=NA)

verbose

boolean Verbose output (default=TRUE)

...

Additional inputs passed to sccore::plapply(), see man for description.

Value

ggplot2 object

Examples

# NOT RUN {
library(dplyr)
## Create merged count matrix
## In this example, cms is a list of count matrices from, e.g., Cellranger count, 
## where cells are in columns and genes in rows
## cm <- sccore:::mergeCountMatrices(cms, transposed = FALSE) %>% Matrix::t()

## If coming from Conos, this can be extracted like so
## cm <- conos.obj$getJointCountMatrix(raw = FALSE) # Either normalized or raw values can be used

## Here, we create a random sparse matrix
cm <- Matrix::rsparsematrix(30,3,0.5) %>% abs(.) %>% 
            `dimnames<-`(list(1:30,c("gene1","gene2","gene3")))

## Create marker vector
markers <- c("gene1","gene2","gene3")

## Additionally, color vectors can be included. 
## These should have the same length as the input (markers, cell groups) 
## Otherwise, they are recycled
col.markers <- c("black","black","red") # or c(1,1,2)
col.clusters <- c("black","red","black") # or c(1,2,1)

## Create annotation vector
annotation <- c(rep("cluster1",10),rep("cluster2",10),rep("cluster3",10)) %>% 
    factor() %>% setNames(1:30)

## Plot. Here, the expression colours range from gray (low expression) to purple (high expression)
sccore:::dotPlot(markers = markers, count.matrix = cm, cell.groups = annotation, 
    marker.colour = col.markers, cluster.colour = col.clusters, cols=c("gray","purple"))

# }