DOI: 10.5061/dryad.76hdr7t39
title: Data from: Biological sex differences in sleep of male and female c57bl/6 mice

description: Sleep is used as a physiological outcome in research, however, few studies
 have disaggregated sleep data based on sex. We investigated biological sex
 differences in sleep under normal physiological conditions using male and
 female C57BL/6 mice (n = 267 from 17 cohorts). Physiological parameters
 were recorded for 48-hours (2 days) using non-invasive piezoelectric cages
 to determine total sleep, non-rapid eye movement (NREM) sleep, rapid eye
 movement (REM) sleep, and wakefulness (WAKE). To investigate sleep
 differences between sexes we fit hierarchical generalized linear mixed
 models with nonlinear time effects. We found substantial sex differences
 in the sleep of C57BL/6 mice. Female mice slept less overall, specifically
 during the dark period, with less NREM sleep compared to males. Females
 also exhibited more REM sleep and WAKE. Females had shorter total and NREM
 sleep bout lengths compared to males. During the light period, REM bout
 lengths and WAKE bout lengths were similar between sexes; however, females
 had longer REM and WAKE bouts during the dark period. Variation in all
 outcomes was nominal between days and among cohorts, demonstrating rigor
 and replicability of our findings. Based on these substantial sex
 differences in sleep, failure to include both sexes in experimental
 designs or appropriately account for sex during analysis could lead to
 flawed inferences and inaccurate translational recommendations in
 pre-clinical sleep studies.
description: Adult (8-20 weeks-old) male and female C57BL/6 mice from 17 total
 sex-specific cohorts were used (males <em>n </em>= 140;
 females <em>n </em>= 127). All mice were bred in-house from
 breeder pairs obtained from Jackson Laboratories (Bar Harbor, ME). For all
 studies, mice were singly housed and maintained on a 12-hour light:dark
 cycle (200 lux, cool white, fluorescent light) at an ambient temperature
 of 24°C ± 2°C. All mice were acclimated to non-invasive piezoelectric
 sleep cages for a minimum of 5 days prior to initiation of data collection
 and were fed a normal diet of standard rodent chow, and food and water
 were available <em>ab libitum</em>. Physiological parameters
 were recorded for 48-hours using non-invasive piezoelectric cages to
 determine total sleep, non-rapid eye movement (NREM) sleep, rapid eye
 movement (REM) sleep, and wakefulness (WAKE).The non-invasive
 piezoelectric cage system used Polyvinylidine Difluoride sensors on the
 cage floor to measure movement and breathing patterns. The piezoelectric
 signals were analyzed over ten-second windows (epochs) at a two-second
 interval. Data collected from the sleep cages were binned at each hour
 using a rolling average of the percentage of recording time spent in
 sleep. Data were also binned by length of individual bout to calculate the
 hourly mean bout length (duration in seconds). To be considered a bout, a
 minimum of two consecutive epochs had to be scored as sleep (or wake).
 Total minutes slept within each experimental period
 (<em>e.g.,</em> day 1) was also calculated. Total sleep was
 determined using Sleep Stats Version 2.18 to compute a decision statistic
 that classified epochs using a linear discriminate classier (‘sleep’ or
 ‘wake’). In addition to total sleep based on a two-state algorithm, a
 decision tree classifier was used to classify WAKE, NREM, and REM using
 Sleep Stats Data Explorer Version 4.
description: # Data From: Biological Sex Differences in Sleep of Male and Female
 C57BL/6 Mice
 [https://doi.org/10.5061/dryad.76hdr7t39](https://doi.org/10.5061/dryad.76hdr7t39) ## Description of the data and file structure **Sex_Differences_Sleep.csv**:  File containing all sleep data from two continuous days under normal physiological conditions. animal_ID – Unique identifier for individual mice. Cohort – Categorical variable denoting the experimental cohort each mouse was in. Sex – Biological sex of mouse Timepoint – Sleep was measured for 2 consecutive days. Categorical variable where ‘A’ denotes the first 24 h and ‘B’ denotes the second 24 h. Time – Categorical variable denoting the time of day (hour) that sleep-wake data were collected. ZT – Categorical variable denoting zeitgeber time (ZT) where ZT0 was the time the lights in the housing room were turned on and ZT12 was lights off. LD Cycle – Categorical variable denoting the light (L) or dark (D) cycle for each hour data were collected. Percent_sleep – Continuous variable of the percent of each hour a mouse spent sleeping (%). Percent_sleepdec – Continuous variable of the percent of each hour a mouse spent sleeping converted to a decimal between 0 and 1. Mean_bout – Integer variable of mean bout length of sleep (seconds) for each hour. Mean_bout_round – Integer variable of mean bout length of sleep (seconds) for each hour rounded to the nearest whole integer. Total_min – Integer variable of the number of minutes a mouse spent asleep during each hour. Total_min_round – Integer variable of the number of minutes a mouse spent asleep during each hour rounded to the nearest whole integer. REM_percent_sleep – Continuous variable of the percent of each hour a mouse spent in rapid eye movement (REM) sleep. REM_percent_sleepdec – Continuous variable of the percent of each hour a mouse spent in rapid eye movement (REM) sleep converted to a decimal between 0 and 1. REM_mean_bout – Integer variable of mean bout length of rapid eye movement (REM) sleep (seconds) for each hour. REM_mean_bout_round – Integer variable of mean bout length of rapid eye movement (REM) sleep (seconds) for each hour rounded to the nearest whole integer. REM_total_min – Integer variable of the number of minutes a mouse spent in rapid eye movement (REM) sleep during each hour. REM_total_min_round – Integer variable of the number of minutes a mouse spent in rapid eye movement (REM) sleep during each hour rounded to the nearest whole integer. nREM_percent_sleep – Continuous variable of the percent of each hour a mouse spent in non-rapid eye movement (nREM) sleep. nREM_percent_sleepdec – Continuous variable of the percent of each hour a mouse spent in non-rapid eye movement (nREM) sleep converted to a decimal between 0 and 1. nREM_mean_bout – Integer variable of mean bout length of non-rapid eye movement (nREM) sleep (seconds) for each hour. nREM_mean_bout_round – Integer variable of mean bout length of non-rapid eye movement (nREM) sleep (seconds) for each hour rounded to the nearest whole integer. nREM_total_min – Integer variable of the number of minutes a mouse spent in non-rapid eye movement (nREM) sleep during each hour. nREM_total_min_round – Integer variable of the number of minutes a mouse spent in non-rapid eye movement (nREM) sleep during each hour rounded to the nearest whole integer. WAKE_percent– Continuous variable of the percent of each hour a mouse spent awake. WAKE_percent_dec – Continuous variable of the percent of each hour a mouse spent awake converted to a decimal between 0 and 1. WAKE_mean_bout – Integer variable of mean bout length of wake episode (seconds) for each hour. WAKE_mean_bout_round – Integer variable of mean bout length of wake episode (seconds) for each hour rounded to the nearest whole integer. WAKE_total_min – Integer variable of the number of minutes a mouse spent awake during each hour. WAKE_total_min_round – Integer variable of the number of minutes a mouse spent awake during each hour rounded to the nearest whole integer. ## Code/Software We fit all statistical models in the frequentist framework using the package ‘glmmTMB’ in the R statistical computing environment. Because outcome measures of interest were either percentages (*e.g.,* percent recording time) or overdispersed counts (*e.g.,* bout lengths and total minutes slept), we specified Beta or negative-binomial error distributions, respectively, in the models. We included three-knot and five-knot basis splines for all sleep time and sleep architecture models, respectively, to accommodate both the expected similarity among observations within a period and the nonlinear effects of time. To determine the appropriate number of spline knots for each sleep time and sleep bout length model, we fit models with two to seven spline knots, conducted model selection using Akaike’s Information Criterion corrected for small sample size (AIC*c*), and produced estimates from the top-ranked, most parsimonious model that best described the data for each outcome.