Introduction

lagci is an R package designed for calculating lagged correlations between two time-series datasets, with a particular focus on wearable and omics data analysis. Developed by Dr. Xiaotao Shen, this tool is available on GitHub at https://github.com/jaspershen-lab/lagci .

lagci is part of the larger tidywearable ecosystem, which provides a comprehensive suite of tools for wearable data analysis. This integration ensures compatibility and workflow continuity for researchers working with multiple types of temporal health data.

The package includes demonstration datasets that illustrate typical use cases: heart_data containing heart rate measurements and step_data containing step count measurements. These datasets exemplify the type of wearable device data that researchers commonly need to analyze for temporal relationships.

Contacts

xiaotao.shen@outlook.com

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Experimental Medicine Building (EMB), 59 Nanyang Dr, Singapore 636921

@ARTICLE{Shen2019-xv, title = "Metabolic reaction network-based recursive metabolite annotation for untargeted metabolomics", author = "Shen, Xiaotao and Wang, Ruohong and Xiong, Xin and Yin, Yandong and Cai, Yuping and Ma, Zaijun and Liu, Nan and Zhu, Zheng-Jiang", journal = "Nat. Commun.", publisher = "Springer Science and Business Media LLC", volume = 10, number = 1, pages = "1516", month = apr, year = 2019, copyright = "https://creativecommons.org/licenses/by/4.0", language = "en" }
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