QCplot {umiAnalyzer}

Generate QC plots

Description

Visualize the UMI count for each selected assay and sample for a given consensus depth. This is useful to detect differences in coverage, especially for multiplexed assays.

Usage

QCplot(
  object,
  group.by = "sample",
  plotDepth = 3,
  assays = NULL,
  samples = NULL,
  theme = "classic",
  option = "viridis",
  direction = "default",
  toggle_mean = TRUE,
  center = "mean",
  line_col = "blue",
  angle = 0,
  plotly = FALSE
)

Arguments

object

Requires a UMI sample or UMI experiment object

group.by

String. Which variable should be used as a factor on the x-axis. Default is sample

plotDepth

Which consensus depth to plot

assays

(Optional) user-supplied list of assays to plot. Default is all.

samples

(Optional) user-supplied list of samples to plot. Default is all.

theme

ggplot theme to use.

option

Color palette to use, either ggplot default or viridis colors.

direction

If viridis colors are used, choose orientation of color scale.

toggle_mean

Show mean or median

center

Choose mean or median

line_col

Choose color for mean/median line

angle

Angle of labels on x-axis.

plotly

Should plotly be used for rendering?

Value

A ggplot object

Examples

library(umiAnalyzer)

main = system.file('extdata', package = 'umiAnalyzer')
samples <- list.dirs(path = main, full.names = FALSE, recursive = FALSE)
simsen <- createUmiExperiment(experimentName = 'example',mainDir = main,sampleNames = samples)

depth_plot <- QCplot(simsen)