#!/usr/bin/Rscript

# Supplementary Data 10. R wrapper script used to generate the sleep and activity phenotypes described in the manuscript "Genetic studies of accelerometer-based sleep measures yield new insights into human sleep behaviour".

graphics.off()
runviabashscript = FALSE
f0 = 1 #file to start with if used in serial analyses
f1 = 999 #file to end with if used in serial analyses (modify accordingly, if infinite then it will process until last file)

mode=c(1,2,3,4) #What part of the analysis needs to be done (options: 1,2,3,4)

library(methods)
require(GGIR)

g.shell.GGIR(#=======================================
             # INPUT NEEDED:
             #-------------------------------
             # General parameters
             #-------------------------------
             mode=mode, #specify above
             datadir="/tmp/inputwavdir", #specify above
             outputdir="/tmp/GGIR_output", #specify above
             studyname="UKBiobank_batch1", #specify above
             f0=f0, #specify above
             f1=f1, #specify above
             overwrite = FALSE, #overwrite previous milestone data?
             do.imp=TRUE, # Do imputation? (recommended)
             idloc=1, #id location (1 = file header, 2 = filename)
             print.filename=TRUE,
             storefolderstructure = FALSE,
             #-------------------------------
             # Part 1 parameters:
             #-------------------------------
             # Key functions: reading file, auto-calibration, and extracting features
             windowsizes = c(5,900,3600), #Epoch length, non-wear detection resolution, non-wear detection evaluation window
             do.cal=TRUE, # Apply autocalibration? (recommended)
             do.enmo = TRUE, #Needed for physical activity analysis
             do.anglez=TRUE, #Needed for sleep detection
             chunksize=1, #size of data chunks to be read (value = 1 is maximum)
             printsummary=TRUE,
             #-------------------------------
             # Part 2 parameters:
             #-------------------------------
             # Key functions: Non-wear detection, imputation, and basic descriptives
             strategy = 2, #Strategy (see tutorial for explanation)
             ndayswindow=7, #only relevant when strategy = 3
             hrs.del.start = 1, # Only relevant when strategy = 2. How many HOURS need to be ignored at the START of the measurement?
             hrs.del.end = 1, # Only relevant when strategy = 2. How many HOURS need to be ignored at the END of the measurement?
             maxdur = 9, # How many DAYS of measurement do you maximumally expect?
             includedaycrit = 16, # number of minimum valid hours in a day to attempt physical activity analysis
             L5M5window = c(0,24), #window over which to calculate L5 and M5
             M5L5res = 10, #resolution in minutes of M5 and L5 calculation
             inhr = c(5,10), # size of M5 and L5 (5 hours by default)
             qlevels = c(c(1380/1440),c(1410/1440)), #quantiles to calculate, set value at c() if you do not want quantiles
             qwindow=c(0,24), #window over which to calculate quantiles
             ilevels = c(0,45.2,93.2,150,8000), #acceleration values (metric ENMO) from which a frequency distribution needs to be derived, set value at c() if you do not want quantiles
             mvpathreshold =c(100,120), #MVPA (moderate and vigorous physical activity threshold
             mvpadur=c(0,1,3,5,10),
             #-------------------------------
             # Part 3 parameters:
             #-------------------------------
             # Key functions: Sleep detection
             timethreshold= c(5), #10
             anglethreshold=5,
             ignorenonwear = TRUE, # if TRUE non-wear is not detected as sleep (if FALSE then it will work with imputed data)
             #-------------------------------
             # Part 4 parameters:
             #-------------------------------
             # Key functions: Integrating sleep log (if available) with sleep detection, storing day and person specific summaries of sleep
             excludefirstlast = FALSE, # Exclude first and last night for sleep analysis?
             includenightcrit = 16, # number of minimum valid hours in a day to attempt sleep analysis
             def.noc.sleep = 1,
             # If sleep log is available:
             # loglocation= "D:/accelerometry/GGIR in development_v2/sleep logs/ucl/sleeplog_corrected_v5.csv", # full directory and name of the log (if available, otherwise leave value as c() )
             outliers.only = TRUE,
             criterror = 4,
             relyonsleeplog = FALSE,
             sleeplogidnum = TRUE, # Is the participant in the sleep log stored as a number (TRUE) or as a character (FALSE)
             colid=1, #colomn in which the participant id or filename is stored
             coln1=2, #column number for first day
             do.visual = TRUE,
             nnights = 9, #number of nights in the sleep log
             #-----------------------------------
             # Report generation
             #-------------------------------
             # Key functions: Generating reports based on meta-data
             do.report=c(2,4,5), #for what parts does and report need to be generated? (option: 2, 4 and 5)
             visualreport=TRUE,
             dofirstpage = TRUE, #first page of pdf-report with simple summary histograms
             viewingwindow=1) #viewingwindow of visual report: 1 centres at day and 2 centers at night