TimeChange: Topology inspired methods for the detection of differential dynamics in time-series data

ABSTRACT: The circadian clock drives the oscillatory expression of thousands of genes across all tissues and bears significant implications for human health. RNA-seq time-series experiments interrogate the mechanistic links between transcriptional rhythms and phenotypic outcomes. Analysis methods must overcome the challenges of sparse temporal sampling, noisy data, and non-strictly periodic dynamics. Moreover, there remains a need for differential cycling analysis methods that can identify complex changes in rhythmicity for 2-sample comparisons across experimental conditions. We present TimeChange -- a non-parametric and model-free method for the quantification of differential dynamics across experimental conditions. The method leverages a data transformation technique known as time-delay embedding to reconstruct the underlying state space for each gene-of-interest. Takens’ embedding theorem implies that rhythmic dynamics will exhibit circular patterns in the embedded space. TimeChange non-parametrically compares the distributions of points in the embedded space via the Fasano-Franceschini test to assess whether the topological structures differ significantly between phenotypes, thereby quantifying differences in transcriptional dynamics without requiring knowledge of the underlying model. Application of TimeChange to synthetic data shows that it accurately identifies changes in transcriptomic dynamics, including differences in amplitude/peaked-ness; changes in sawtooth asymmetries; and trending oscillatory drifts (e.g. linear, damped, and contractile). We further show that the method has potential utility beyond circadian dynamics. For instance, initial tests of TimeChange using erg rowing-machine data shows accurate classification of differential stroke dynamics in real time, suggesting potential uses of TimeChange in the field of sports science and medicine.

ORGANISM(S): Drosophila melanogaster

PROVIDER: GSE193991 | GEO | 2023/06/30

REPOSITORIES: GEO