Analyzing Sleep States with FlyDreamR

The standard way to measure sleep in Drosophila, calling any five-minute stretch of immobility “sleep”, flattens what is almost certainly a richer biological signal. FlyDreamR fits a hidden Markov model to your DAM activity data to recover that signal, classifying each minute of recording into distinct sleep and wake states rather than applying a single arbitrary threshold.

This vignette is a quick roadmap. If you want to get straight to analysis, pick the vignette that matches your goal.

What to read next

• Getting data into FlyDreamR: vignette("data-prep", package = "FlyDreamR")
• Traditional sleep analyses: vignette("traditional-sleep", package = "FlyDreamR")
• HMM fitting and visualization: vignette("hmm-workflow", package = "FlyDreamR")
• Running the Shiny app: vignette("shiny-app", package = "FlyDreamR")

Installation (typical options)

From GitHub (recommended)

# Install from GitHub (devtools or remotes)
install.packages(c('devtools','remotes'), repos='https://cloud.r-project.org')
remotes::install_github('orijitghosh/FlyDreamR', upgrade = 'never')

Then load the package:

library(FlyDreamR)

Getting help

• Check documentation: ?HMMbehavr
• View examples: example(HMMplot)

Citation

If you use FlyDreamR in your research, please cite:

Ghosh A, Harbison ST. Inferring the genetic basis of sleep states in Drosophila melanogaster using hidden Markov models. bioRxiv. 2026: 2026.2001.2014.699526.