Abstract | Using yeast gene expression data we show how correlation can be misleading and present proportionality as a valid alternative for relative data. |
Author Summary | Using timecourse yeast gene expression data , we show how correlation of relative abundances can lead to conclusions opposite to those drawn from absolute abundances, and that its value changes when different components are included in the analysis. |
Introduction | To further illustrate how correlation can be misleading we applied it to absolute and relative gene expression data in fission yeast cells deprived of a key nutrient [6]. |
Conclusions | In this paper, we compare methods for detecting rhythmic time series in genome-wide expression data . |
Discussion | These approaches are general and can be applied to detecting periodic behavior in a wide range of contexts, but we focus on time series representative of genome-wide expression data . |
Discussion | [28] recently reviewed a number of earlier studies of rhythm detection methods and selected four algorithms for comparison (de Lichtenberg, Lomb-Scargle, ITK_CYCLE, and persistent homology) based on their mathematical properties and applicability to genome-wide expression data . |