Plot Longitudinal Samples by Subject

A samples plot by grouping the subjects across time in a longitudinal study. Can be as few as two longitudinal samples (e.g. paired samples). See examples for various plotting options. In order to generate a longitudinal plot by sample, 4 variables (columns of the data frame data) must be provided:

• y: Typically the field containing the y-axis.

• time: The field containing the time-series information, the x-axis.

• id: The field containing subject identifiers, i.e. how the points in each line should be connected.

• color.by (optional): A field describing how groups should be split/colored. The only argument with a default value.

Usage

plotLongitudinal(
  data,
  y,
  time,
  id,
  color.by = NULL,
  size = 2.5,
  summary.line = stats::median,
  main = NULL,
  y.lab = NULL,
  x.lab = NULL,
  add.box = FALSE
)

Arguments

data

A data frame containing RFU values to plot, typically a soma_adat class object.

y

A quoted or unquoted variable name in data for the column containing the y-axis (i.e. typically the "Response" variable).

time

A quoted or unquoted variable name in data for the column containing the x-axis (i.e. typically the "time" variable).

id

A quoted or unquoted variable name in data for the column containing the subject IDs (i.e. how the samples should be connected).

color.by

A quoted or unquoted variable name in data for the column indicating how to color/group the lines.

size

Numeric. The size for the points on the subject lines.

summary.line

A function describing how to summarize the lines. Typically base::mean() or stats::median(), but can be any function that takes a numeric vector and returns a scalar. To suppress, set to NULL.

main

Character. Main title for the plot. See ggtitle() for ggplot2 style graphics.

y.lab

Character. Optional string to set the y-axis label. Defaults to log10(RFU) if a SeqId name is detected for y.

x.lab

Character. Optional string for the x-axis. Otherwise one is automatically generated (default).

add.box

Logical. Should boxplots be drawn for each time point? Note: this groups the subjects together by time point, thus the time variable must be a factor.

Value

A longitudinal plot of samples by subject.

See also

geom_line(), theme()

Author

Stu Field

Examples

fct_vec <- factor(c("baseline", "6 months", "12 months", "24 months"))
levels(fct_vec) <- fct_vec
df <- withr::with_seed(100,
  data.frame(
    sample_id   = rep(1:10L, times = 4L),
    pop         = rep_len(utils::head(LETTERS, 10L), 40L),
    time_point  = rep(fct_vec, each = 10L),
    seq.1234.56 = stats::rnorm(40, mean = 25, sd = 3.5)
  )
)

# Map 'time_point' (chr) to 'time_dbl' (numeric)
new <- df |>
 dplyr::left_join(
   data.frame(time_point = fct_vec, time_dbl = c(0, 6, 12, 24)),
   by = "time_point"
 ) |>
 # code 'size' to correlate with IDs
 dplyr::mutate(size = dplyr::case_when(sample_id <= 4 ~ "small",
                                        sample_id > 7 ~ "large",
                                                 TRUE ~ "medium"))

# No title; no x-axis label; nothing fancy
plotLongitudinal(new, y = "seq.1234.56", time = "time_point", id = "sample_id")


# Color lines by the 'size' variable
plotLongitudinal(new, y = "seq.1234.56", time = "time_point", id = "sample_id",
                 color.by = "size")


# Color lines by the 'size' variable, using the 'time_dbl' x-variable
plotLongitudinal(new, y = "seq.1234.56", time = "time_dbl", id = "sample_id",
                 color.by = "size")


# Can use unquoted variable names
plotLongitudinal(new, y = seq.1234.56, time = time_dbl, id = sample_id,
                 color.by = size)


# Summary lines
plotLongitudinal(new, y = seq.1234.56, id = sample_id, time = time_dbl,
                 color.by = size, summary.line = base::mean,
                 main = "Use `mean()` Summary")


plotLongitudinal(new, y = seq.1234.56, id = sample_id, time = time_dbl,
                 color.by = size, summary.line = NULL,
                 main = "Suppress Summary Lines")


plotLongitudinal(new, y = seq.1234.56, id = sample_id, time = time_dbl,
                 color.by = size, summary.line = function(x) 15,
                 main = "Fixed Summary (y = 15)")


# Add boxplots by time point
plotLongitudinal(new, seq.1234.56, id = sample_id, time = time_point,
                 color.by = size, add.box = TRUE, summary.line = NULL,
                 main = "With Time Point Boxplots")


# Facet by `size`
plotLongitudinal(new, y = seq.1234.56, id = sample_id, time = time_dbl,
                 color.by = size, summary.line = base::mean,
                 main = "Split by 'size'") +
  ggplot2::facet_wrap(~ size)