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LimoRhyde2: genomic analysis of biological rhythms based on effect sizes
Dora Obodo1,2, Elliot H Outland1, Jacob J Hughey1,2,3
1Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
Biorxiv : the Preprint Server for Biology
|February 13, 2023
Summary
LimoRhyde2 quantifies biological rhythm effect sizes, not just statistical significance. This new method prioritizes genes with high-amplitude daily rhythms, improving genomic data interpretation.
Area of Science:
- Genomics
- Chronobiology
- Bioinformatics
Background:
- Genome-scale data reveal daily rhythms in biological systems.
- Current methods for assessing rhythmicity often prioritize statistical significance over biological relevance.
- A need exists for methods that quantify rhythm-related effect sizes and their uncertainty.
Approach:
- Developed LimoRhyde2, a novel method focusing on rhythm-related effect sizes.
- Utilizes periodic splines to model non-sinusoidal rhythms and Empirical Bayes (Mash) for fit moderation.
- Calculates rhythm statistics, including peak-to-trough amplitude, from moderated fits.
Key Points:
- LimoRhyde2 prioritizes genes with high-amplitude expression rhythms.
- Contrasts with prior methods that may prioritize statistically significant but low-amplitude rhythms.
- Demonstrated utility on multiple circadian transcriptome datasets.
Conclusions:
- Quantifying effect sizes, as enabled by LimoRhyde2, offers a more biologically relevant interpretation of genomic rhythm data.
- LimoRhyde2 has the potential to transform the analysis of circadian transcriptomes and other rhythmic genomic data.
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