The SomaPlotr R package contains various standardized plotting
functions designed to visualize SomaScan data in the R statistical
environment. SomaPlotr is based on the “Grammar of Graphics”
(Wilkinson,
2005), the same
layered framework of mapping variables to aesthetics that provides a
structure for ggplot2. As
such, SomaPlotr largely utilizes ggplot-style syntax, and can easily
and quickly create fully labeled, colored figures of SomaScan data.
SomaPlotr is designed to generate figures that are well-suited for the
exploration and visualization of SomaScan data. SomaPlotr is therefore
biased towards cumulative distribution function (CDF) plots, probability
density function (PDF) plots, volcano and concordance plots, grouped
boxplots, and more.
Keep reading (in the Examples section below) to see how
these graphics can be generated using functions in SomaPlotr.
For a full table of the visualizations that can be created with
SomaPlotr, see the Usage section below. For additional
examples and details, see the package vignette
(vignette("SomaPlotr")).
SomaPlotr can be installed from
GitHub using the
remotes package as
follows:
remotes::install_github("SomaLogic/SomaPlotr")To load SomaPlotr, simply make a call to library():
library(SomaPlotr)SomaPlotr provides tools to create figures commonly used for the
visualization of SomaScan data. While the package does not include a
comprehensive list of all possible graphics, those that it does
contain are popular for exploring and analyzing patterns in SomaScan.
The table below provides a high-level summary of the graphics that can
be created with SomaPlotr:
| Plot type | Description | Function(s) |
|---|---|---|
| CDF | Empirical cumulative distribution function | plotCDF(), plotCDFlist(), plotCDFbyGroup() |
| Probability density function | plotPDF(), plotPDFlist(), plotCDFbyGroup() |
|
| Volcano | Statistical significance vs. magnitude of fold change | plotVolcano(), plotVolcanoHTML() |
| Concordance | Correlation coefficients of values in numeric vectors x and y |
plotConcord() |
| Histogram | Frequency distribution of numeric data | plotDoubleHist() |
| Boxplot | Locality, spread and skewness of numeric data via quartiles | boxplotBeeswarm(), boxplotGrouped(), boxplotSubarray() |
| Longitudinal | Graphical representation of numeric data over time, by subject (also called a “trace plot”) | plotLongitudinal() |
The plotting functions in SomaPlotr require a SomaScan dataset as
input, and generate a complete, labeled figure that can be further
customized and modified, if desired.
Using SomaPlotr, the previously shown boxplot comparing RFU values
across groups can be generated via boxplotGrouped():
# Simulate an example dataset
timepoint <- c("Treatment", "Relapse", "Remission")
withr::with_seed(101, {
clin_df <- data.frame(
TimePoint = sample(timepoint, 80, replace = TRUE),
seq.1234.56 = stats::rnorm(80, mean = 12, sd = 5)
)
})
# Create grouped boxplot w/ customized title
boxplotGrouped(
clin_df,
y = "seq.1234.56",
group.var = "TimePoint",
beeswarm = TRUE,
main = "Box Plot of Sample Timepoint"
)
Similarly, we can replicate the CDF plot in the introductory figure
above via plotCDF():
x <- withr::with_seed(101, rnorm(100, mean = 4))
cdf <- plotCDF(x)
cdf
A quantile/percentile line (the red line
in the figure below) can be added to an existing CDF plot via
addCDFquantiles():
cdf + addCDFquantiles(x, col = "red")
For a more in-depth overview of the package and a full list of example
plots, please see the package vignette: vignette("SomaPlotr").
SomaPlotr provides color palettes that correspond to SomaLogic
Operating Co., Inc. company color schemes:
scales::show_col(palette_soma(n = 8))
These palettes can be incorporated into figures in a variety of ways.
The soma_colors and soma_colors2 objects provide individual hex
colors for the SomaLogic color scheme. These objects can be used to
transform the ggplot2 default color
palette.
data.frame(x = seq_along(soma_colors2), y = seq_along(soma_colors2)) |>
ggplot(aes(x = x, y = y)) +
geom_bar(stat = "identity", fill = soma_colors2) +
scale_x_discrete(labels = names(soma_colors2)) +
theme(axis.title.y = element_blank(),
axis.text.y = element_blank(),
axis.ticks.y = element_blank())
The theme_soma() theme and scale_color_soma() functions provide a
uniform plotting and color scheme. By using the theme_soma() theme,
polished, publication ready figures can be generated with consistent
font sizes, backgrounds, legend positions, and more.
Below, the left plot (p1) was created with the mtcars data set,
using all ggplot2 defaults. The right plot (p2) uses the same data
set, but with the theme_soma() theme and scale_color_soma() color
scale applied.
p1 <- ggplot(mtcars, aes(x = hp, y = mpg, color = factor(cyl))) +
geom_point(alpha = 0.5, size = 4)
p2 <- p1 +
theme_soma() +
scale_color_soma()
More detailed examples illustrating how to apply these themes can be
found in vignette("themes-and-palettes"). For a full list of available
color scales and themes, see ?SomaPlotr::theme_soma.
- See:
- The MIT license:
- Further:
- “SomaPlotr” and “SomaLogic” are trademarks owned by SomaLogic Operating Co., Inc. No license is hereby granted to these trademarks other than for purposes of identifying the origin or source of this Software.
