{ "_id": "6a2cf21c3efcd9bda42e3e98", "Package": "mMARCH.AC", "Version": "3.3.4.0", "Date": "2026-2-5", "Title": "Processing of Accelerometry Data with 'GGIR' in mMARCH", "Authors@R": "c(\nperson(given = \"Wei\", family = \"Guo\",\nrole = c(\"aut\", \"cre\"), email = \"wei.guo3@nih.gov\"),\nperson(given = \"Andrew\", family = \"Leroux\",\nrole = c(\"aut\"), email = \"andrew.leroux@cuanschutz.edu\"),\nperson(given = \"Vadim\", family = \"Zipunnikov\",\nrole = c(\"aut\"), email = \"vzipunni@jhsph.edu\"),\nperson(given = \"Kathleen\", family = \"Merikangas\",\nrole = c(\"aut\"), email = \"merikank@mail.nih.gov\")\n)", "Maintainer": "Wei Guo ", "Description": "Mobile Motor Activity Research Consortium for Health\n(mMARCH) is a collaborative network of studies of clinical and\ncommunity samples that employ common clinical, biological, and\ndigital mobile measures across involved studies. One of the\nmain scientific goals of mMARCH sites is developing a better\nunderstanding of the inter-relationships between\naccelerometry-measured physical activity (PA), sleep (SL), and\ncircadian rhythmicity (CR) and mental and physical health in\nchildren, adolescents, and adults. Currently, there is no\nconsensus on a standard procedure for a data processing\npipeline of raw accelerometry data, and few open-source tools\nto facilitate their development. The R package 'GGIR' is the\nmost prominent open-source software package that offers great\nfunctionality and tremendous user flexibility to process raw\naccelerometry data. However, even with 'GGIR', processing done\nin a harmonized and reproducible fashion requires a non-trivial\namount of expertise combined with a careful implementation. In\naddition, novel accelerometry-derived features of PA/SL/CR\ncapturing multiscale, time-series, functional, distributional\nand other complimentary aspects of accelerometry data being\nconstantly proposed and become available via non-GGIR R\nimplementations. To address these issues, mMARCH developed a\nstreamlined harmonized and reproducible pipeline for loading\nand cleaning raw accelerometry data, extracting features\navailable through 'GGIR' as well as through non-GGIR R\npackages, implementing several data and feature quality checks,\nmerging all features of PA/SL/CR together, and performing\nmultiple analyses including Joint Individual Variation\nExplained (JIVE), an unsupervised machine learning dimension\nreduction technique that identifies latent factors capturing\njoint across and individual to each of three domains of\nPA/SL/CR. In detail, the pipeline generates all necessary\nR/Rmd/shell files for data processing after running 'GGIR' for\naccelerometer data. In module 1, all csv files in the 'GGIR'\noutput directory were read, transformed and then merged. In\nmodule 2, the 'GGIR' output files were checked and summarized\nin one excel sheet. In module 3, the merged data was cleaned\naccording to the number of valid hours on each night and the\nnumber of valid days for each subject. In module 4, the cleaned\nactivity data was imputed by the average Euclidean norm minus\none (ENMO) over all the valid days for each subject. Finally, a\ncomprehensive report of data processing was created using\nRmarkdown, and the report includes few exploratory plots and\nmultiple commonly used features extracted from minute level\nactigraphy data. Reference: Guo W, Leroux A, Shou S, Cui L,\nKang S, Strippoli MP, Preisig M, Zipunnikov V, Merikangas K\n(2022) Processing of accelerometry data with GGIR in Motor\nActivity Research Consortium for Health (mMARCH) Journal for\nthe Measurement of Physical Behaviour, 6(1): 37-44.", "URL": "https://github.com/WeiGuoNIMH/mMARCH.AC", "BugReports": "https://github.com/WeiGuoNIMH/mMARCH.AC/issues", "License": "GPL-3", "Encoding": "UTF-8", "ByteCompile": "true", "Type": "Package", "VignetteBuilder": "knitr", "RoxygenNote": "7.3.3", "NeedsCompilation": "no", "Packaged": { "Date": "2026-06-11 10:28:28 UTC", "User": "root" }, "Author": "Wei Guo [aut, cre], Andrew Leroux [aut], Vadim Zipunnikov\n[aut], Kathleen Merikangas [aut]", "Config/pak/sysreqs": "cmake libfontconfig1-dev libfreetype6-dev\nlibfribidi-dev make libharfbuzz-dev default-jdk libicu-dev\nlibpng-dev libuv1-dev libxml2-dev zlib1g-dev", "Repository": "https://cranhaven.r-universe.dev", "Date/Publication": "2026-06-11 02:02:00 UTC", 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"committer": "GitHub Action ", "message": "Add mMARCH.AC to CRANhaven, because archived on 2026-06-11 02:02:00 +0000\n", "time": 1781143320 }, "_maintainer": { "name": "Wei Guo", "email": "wei.guo3@nih.gov", "login": "weiguonimh", "description": "Biostatistican in NIMH", "uuid": 62949642 }, "_registered": true, "_dependencies": [ { "package": "R", "version": ">= 3.6.0", "role": "Depends" }, { "package": "refund", "role": "Imports" }, { "package": "denseFLMM", "role": "Imports" }, { "package": "dplyr", "role": "Imports" }, { "package": "xlsx", "role": "Imports" }, { "package": "survival", "role": "Imports" }, { "package": "stats", "role": "Imports" }, { "package": "tidyr", "role": "Imports" }, { "package": "zoo", "role": "Imports" }, { "package": "ineq", "role": "Imports" }, { "package": "cosinor", "role": "Imports" }, { "package": "cosinor2", "role": "Imports" }, { "package": "abind", "role": "Imports" }, { "package": "accelerometry", "role": "Imports" }, { "package": "ActCR", "role": 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