A User-friendly and Powerful R Analysis of Large-scale Datasets
Year: 2025
Type: article
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.
DOI: 10.3791/68868
Authors: Jessica Allison, Chong Zhang, Riki Egoshi, Hua Lu
Institution: University of Maryland, Baltimore County
Language: English
Topic: Data Analysis with R
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4416690610
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