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However, existing tools to analyze circadian data often require coding expertise or rely on specific data acquisition software, limiting their general applicability. Here, we present easyClock, an intuitive and interactive application designed to streamline circadian rhythm analysis and visualization. The easyClock application enables simultaneous processing of multiple files, allowing users to batch-analyze and visualize diverse sets of time series data. To enhance data analysis efficiency and provide comparable results, this application integrates comprehensive methods for handling data with various waveforms and noises. Additionally, easyClock can assess inter-individual variability and group differences using linear mixed-effects modeling. All statistical results and graphs are easily viewed and exported for any selected range of data. As a demonstration, we present a re-analysis of a time-series transcriptomic dataset, highlighting the value of easyClock as an accessible, open-source tool. This easy-to-use application requires no programming expertise and can be directly installed on Windows and macOS machines in a single step.<\/jats:p>","DOI":"10.1186\/s12859-025-06340-9","type":"journal-article","created":{"date-parts":[[2025,12,5]],"date-time":"2025-12-05T14:31:32Z","timestamp":1764945092000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["easyClock: a user-friendly desktop application for circadian rhythm analysis and visualization"],"prefix":"10.1186","volume":"27","author":[{"given":"Binbin","family":"Wu","sequence":"first","affiliation":[]},{"given":"William W.","family":"Ja","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,12,5]]},"reference":[{"key":"6340_CR1","doi-asserted-by":"publisher","first-page":"329","DOI":"10.1038\/417329a","volume":"417","author":"S Panda","year":"2002","unstructured":"Panda S, Hogenesch JB, Kay SA. 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