A User-friendly and Powerful R Analysis of Large-scale Datasets

Large datasets are increasingly common in the scientific field. It is important to develop user-friendly tools to allow researchers to analyze these large datasets with ease. Here, we introduce a method involving an R script in the open-source software RStudio to analyze large-scale datasets obtained from time series experiments. This method requires minimal input from a user, allowing a beginner who does not have prior R knowledge or programming experience to use it. The detailed instructions described here and in the R script shall further guide users on how to use the method. The input data and the output results are stored in the same folder of a local computer, making it possible to do the analysis anywhere and anytime. The output results are organized into folders for easy interpretation, and they can be conveniently processed to generate figures for publications. This method has been successfully used to analyze circadian clock data and reactive oxygen species burst data, both containing large-scale datasets from time series experiments in a 96-well-plate format. We believe that this method provides a facile and powerful solution for researchers in analyzing similar large datasets obtained through time series experiments.

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Publication Details

Journal
Journal of Visualized Experiments
Published
2025-11-04
DOI
https://doi.org/10.3791/68868
Primary Topic
Circadian rhythm and melatonin
Type
article
Field-Weighted Citation Impact
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article

A User-friendly and Powerful R Analysis of Large-scale Datasets

Jessica Allison, Riki Egoshi, Hua Lü, Chong Zhang
Journal of Visualized Experiments
Circadian rhythm and melatonin
article

A User-friendly and Powerful R Analysis of Large-scale Datasets

Jessica Allison, Riki Egoshi, Hua Lü, Chong Zhang
article en

Abstract

Large datasets are increasingly common in the scientific field. It is important to develop user-friendly tools to allow researchers to analyze these large datasets with ease. Here, we introduce a method involving an R script in the open-source software RStudio to analyze large-scale datasets obtained from time series experiments. This method requires minimal input from a user, allowing a beginner who does not have prior R knowledge or programming experience to use it. The detailed instructions described here and in the R script shall further guide users on how to use the method. The input data and the output results are stored in the same folder of a local computer, making it possible to do the analysis anywhere and anytime. The output results are organized into folders for easy interpretation, and they can be conveniently processed to generate figures for publications. This method has been successfully used to analyze circadian clock data and reactive oxygen species burst data, both containing large-scale datasets from time series experiments in a 96-well-plate format. We believe that this method provides a facile and powerful solution for researchers in analyzing similar large datasets obtained through time series experiments.

Journal of Visualized Experiments(225)
University of Maryland, Baltimore County (US)
Openalex Percentile: Top 63%
Circadian rhythm and melatonin
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