Plot biomarkers by batch

To provide a simple visualization of potential batch effects, plot_batch generates a Tukey box plot overlaid by a jittered dot plot, inspired by the Stata plugin stripplot.

Boxes span from the 1st to the 3rd quartile; thick lines indicate medians; whiskers span up to 1.5 times the interquartile range; and asterisks indicate means.

plot_batch(
  data,
  marker,
  batch,
  color = NULL,
  maxlevels = 15,
  title = NULL,
  ...
)

Arguments

data

Dataset.

marker

Variable indicating the biomarker.

batch

Variable indicating the batch.

color

Optional: third variable to use for symbol color and shape. For example, color can be used to show differences in a confounder.

maxlevels

Optional: Maximum number of levels for color parameter to accept as a discrete variable, rather than a continuous variable. Defaults to 15.

title

Optional: character string that specifies plot title

...

Optional: Passed on to ggplot.

Value

ggplot2 object, which can be further modified using standard ggplot2 functions. See examples.

References

Cox NJ (2003). STRIPPLOT: Stata module for strip plots (one-way dot plots). Statistical Software Components S433401, Boston College Department of Economics, revised 11 Oct 2020.

Manimaran S, Selby HM, Okrah K, Ruberman C, Leek JT, Quackenbush J, Haibe-Kains B, Bravo HC, Johnson WE (2016). BatchQC: interactive software for evaluating sample and batch effects in genomic data. Bioinformatics. doi:10.1093/bioinformatics/btw538

See also

More powerful visualizations of batch effects exist in the BatchQC package:

http://bioconductor.org/packages/release/bioc/html/BatchQC.html

Examples

# Define example data
df <- data.frame(
  tma = rep(1:2, times = 10),
  biomarker = rep(1:2, times = 10) +
    runif(max = 5, n = 20),
  confounder = rep(0:1, times = 10) +
    runif(max = 10, n = 20)
)

# Visualize batch effects:
plot_batch(
  data = df,
  marker = biomarker,
  batch = tma,
  color = confounder
)


# Label y-axis, changing graph like other ggplots:
plot_batch(
  data = df,
  marker = biomarker,
  batch = tma,
  color = confounder
) +
  ggplot2::labs(y = "Biomarker (variable 'noisy')")