LimoRhyde2: genomic analysis of biological rhythms based on effect sizes

• DOI: 10.1101/2023.02.02.526897
• Publication Date: 2023-02-04T07:35:18Z
• Authors: Dora Obodo; Elliot H. Outland; Jacob J. Hughey
• Keywords: 0303 health sciences; Genome; Science; Q; R; Bayes Theorem; Genomics; Article; Circadian Rhythm; 03 medical and health sciences; Medicine; Transcriptome; Research Article

Genome-scale data have revealed daily rhythms in various species and tissues. However, current methods to assess rhythmicity largely restrict their focus quantifying statistical significance, which may not reflect biological relevance. To address this limitation, we developed a method called LimoRhyde2 (the successor our LimoRhyde), focuses instead on rhythm-related effect sizes uncertainty. For each genomic feature, fits curve using series of linear models based periodic splines, moderates the an Empirical Bayes approach multivariate adaptive shrinkage (Mash), then uses moderated calculate rhythm statistics such as peak-to-trough amplitude. The splines capture non-sinusoidal rhythmicity, while Mash patterns account for different having levels noise. demonstrate LimoRhyde2's utility, applied it multiple circadian transcriptome datasets. Overall, prioritized genes high-amplitude expression, whereas prior (BooteJTK) "statistically significant" whose amplitudes could be relatively small. Thus, approaches has potential transform interpretation related rhythms.