Traditional sleep analyses

This vignette demonstrates FlyDreamR’s “traditional” sleep workflow using calcTradSleep().

Prepare data with a sleep definition

FlyDreamR lets you define sleep as immobility bouts of a minimum duration (e.g., 5 minutes, 60 minutes). Start by preparing the dataset with HMMDataPrep() and a chosen min_time_immobile definition.

# Load demo data
meta_file <- system.file("extdata", "Metadata_Monitor1.csv", package = "FlyDreamR")
data_dir <- system.file("extdata", package = "FlyDreamR")
# 5-minute sleep definition
dt_5min <- HMMDataPrep(
  metafile_path = meta_file,
  result_dir    = data_dir,
  ldcyc              = 12,
  day_range          = c(1, 2),
  min_time_immobile  = c(behavr::mins(5), behavr::mins(1440))
)

trad_5min <- calcTradSleep(dt_5min)
trad_5min

# 60-minute sleep definition
dt_60min <- HMMDataPrep(
  metafile_path = meta_file,
  result_dir    = data_dir,
  ldcyc              = 12,
  day_range          = c(1, 2),
  min_time_immobile  = c(behavr::mins(60), behavr::mins(1440))
)

trad_60min <- calcTradSleep(dt_60min)
trad_60min

calcTradSleep() returns a list of summary tables, including day/night breakdowns and bout/latency statistics.

Plotting somnograms and sleep/activity profiles

A common plotting workflow uses ggetho (for ethograms/profiles) and ggplot2 for summary visualizations.

library(ggplot2)
library(ggetho)

# Somnogram-like ethogram
ggetho::ggetho(dt_5min, mapping = aes(x = t, z = asleep)) +
  ggetho::stat_bar_tile_etho()

# Sleep profile by genotype
ggetho::ggetho(dt_5min, mapping = aes(x = t, y = asleep, color = genotype)) +
  ggetho::stat_pop_etho()

# Facet by genotype + LD annotations
ggetho::ggetho(dt_5min, mapping = aes(x = t, y = asleep, color = genotype)) +
  ggetho::stat_pop_etho() +
  ggplot2::facet_grid(genotype ~ .) +
  ggetho::stat_ld_annotations()

Plot summary sleep time by day/night

ggplot2::ggplot(trad_5min$sleep_summary_phase,
                ggplot2::aes(x = genotype, y = time_spent_sleeping, fill = genotype)) +
  ggplot2::geom_boxplot(width = 0.35, outliers = FALSE) +
  ggplot2::facet_grid(phase ~ day, scales = "free_y") +
  ggplot2::theme_minimal()