ArticleNature communications2024
tauFisher predicts circadian time from a single sample of bulk and single-cell pseudobulk transcriptomic data.
Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Chrono-atlas of cell-type specific daily gene expression rhythms in the regenerating colon.Nature communications · 2026Article
- D-Box Binding Protein (DBP) as a Circadian Output Regulator: Molecular Mechanisms, Tissue-Specific Functions, and Disease Relevance.International journal of molecular sciences · 2026Review
- Transcriptional noise sets fundamental limits to decoding circadian clock phase from single-cell RNA snapshots.iScience · 2026Article
- Clocking immunity: circadian modulation of NK cells and emerging timing perspectives.Frontiers in immunology · 2026Review
- Article
- Machine learning models highlight environmental and genetic factors associated with the Arabidopsis circadian clock.Nature communications · 2025Article
- Single-Cell Multiomic Analysis of Circadian Rhythmicity in Mouse Liver.bioRxiv : the preprint server for biology · 2025Article
- Designing and Evaluating Circadian Experiments on Mouse Skin.The Journal of investigative dermatology · 2025Review
- Personalization of Cancer Treatment: Exploring the Role of Chronotherapy in Immune Checkpoint Inhibitor Efficacy.Cancers · 2025Review
- Circadian rhythms in cardiovascular (dys)function: approaches for future therapeutics.NPJ cardiovascular health · 2024Review
- tauFisher predicts circadian time from a single sample of bulk and single-cell pseudobulk transcriptomic data.Nature communications · 2024Article
- Current Considerations in the Diagnosis and Treatment of Circadian Rhythm Sleep-Wake Disorders in Children.Seminars in pediatric neurology · 2023Article
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8 authors.
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Abstract
As the circadian clock regulates fundamental biological processes, disrupted clocks are often observed in patients and diseased tissues. Determining the circadian time of the patient or the tissue of focus is essential in circadian medicine and research. Here we present tauFisher, a computational pipeline that accurately predicts circadian time from a single transcriptomic sample by finding correlations between rhythmic genes within the sample. We demonstrate tauFisher's performance in adding timestamps to both bulk and single-cell transcriptomic samples collected from multiple tissue types and experimental settings. Application of tauFisher at a cell-type level in a single-cell RNAseq dataset collected from mouse dermal skin implies that greater circadian phase heterogeneity may explain the dampened rhythm of collective core clock gene expression in dermal immune cells compared to dermal fibroblasts. Given its robustness and generalizability across assay platforms, experimental setups, and tissue types, as well as its potential application in single-cell RNAseq data analysis, tauFisher is a promising tool that facilitates circadian medicine and research.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.