draw_scatterplot: Scatterplot for Gene Expression Values

In insightsengineering/hermes: Preprocessing, analyzing, and reporting of RNA-seq data

Scatterplot for Gene Expression Values

Description

This produces a scatterplot of two genes or gene signatures.

Usage

draw_scatterplot(
  object,
  assay_name,
  x_spec,
  y_spec,
  color_var = NULL,
  facet_var = NULL,
  smooth_method = c("lm", "loess", "none")
)

Arguments

object	(AnyHermesData) input.
assay_name	(string) selects assay from input.
x_spec	(GeneSpec) gene specification for the x-axis.
y_spec	(GeneSpec) gene specification for the y-axis.
color_var	(string or NULL) optional color variable, taken from input sample variables.
facet_var	(string or NULL) optional faceting variable, taken from input sample variables.
smooth_method	(string) smoothing method to use, either linear regression line (lm), local polynomial regression (loess) or none.

Value

The ggplot scatterplot.

Examples

object <- hermes_data
g <- genes(object)

draw_scatterplot(
  object,
  assay_name = "counts",
  facet_var = NULL,
  x_spec = gene_spec(c(A = g[1])),
  y_spec = gene_spec(g[2]),
  color = "RACE"
)

object2 <- object %>%
  add_quality_flags() %>%
  filter() %>%
  normalize()
g2 <- genes(object2)

draw_scatterplot(
  object2,
  assay_name = "tpm",
  facet_var = "SEX",
  x_spec = gene_spec(g2[1:10], colMeans, "Mean"),
  y_spec = gene_spec(g2[11:20], colMedians, "Median"),
  smooth_method = "loess"
)

insightsengineering/hermes documentation built on March 1, 2023, 5:58 a.m.