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postGGIR (version 2.4.0.2)

Data Processing after Running 'GGIR' for Accelerometer Data

Description

Generate all necessary R/Rmd/shell files for data processing after running 'GGIR' (v2.4.0) for accelerometer data. In part 1, all csv files in the GGIR output directory were read, transformed and then merged. In part 2, the GGIR output files were checked and summarized in one excel sheet. In part 3, the merged data was cleaned according to the number of valid hours on each night and the number of valid days for each subject. In part 4, the cleaned activity data was imputed by the average Euclidean norm minus one (ENMO) over all the valid days for each subject. Finally, a comprehensive report of data processing was created using Rmarkdown, and the report includes few exploratory plots and multiple commonly used features extracted from minute level actigraphy data.

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Version

Install

install.packages('postGGIR')

Monthly Downloads

211

Version

2.4.0.2

License

GPL-3

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Maintainer

Wei Guo

Last Published

January 6th, 2022

Functions in postGGIR (2.4.0.2)

IV2

Intradaily Variability
ActCosinor_long2

Cosinor Model for Circadian Rhythmicity for the Whole Dataset
ActCosinor2

Cosinor Model for Circadian Rhythmicity
IS_long2

Interdaily Statbility for the Whole Dataset
ActExtendCosinor_long2

Cosinor Model for Circadian Rhythmicity for the Whole Dataset
ActExtendCosinor2

Extended Cosinor Model for Circadian Rhythmicity
bin_data2

Bin data into longer windows
IS2

Interdaily Statbility
afterggir

Main Call for Data Processing after Runing GGIR for Accelerometer Data
DataShrink

Annotating the merged data for all accelerometer files in the GGIR output
PAfun

Timne Metrics for Whole Dataset
RA_long2

Relative Amplitude for the Whole Datset
RA2

Relative Amplitude
IV_long2

Intradaily Variability for the Whole Dataset
wear_flag

Create Wear/Nonwear Flags
Time_long2

Timne Metrics for Whole Dataset
fragmentation_long2

Fragmentation Metrics for Whole Dataset
fragmentation2

Fragmentation Metrics
Time2

Time of A Certain activity State
SVDmiss2

Modified SVDmiss function (package SpatioTemporal)
data.imputation

Data imputation for the cleaned data with annotation
pheno.plot

View phenotype variables
jive.predict2

Modified jive.predict function (package: r.jive)
create.postGGIR

Create a template shell script of postGGIR
Tvol2

Total Volumen of Activity for Whole Dataset
ggir.datatransform

Transform the data and merge all accelerometer files in the GGIR output
ggir.summary

Description of all accelerometer files in the GGIR output