How to find genes whose expression vary the most in time-series? Hi I am reading this paper and trying to analyse the same datasets in my work:
dynGENIE3: dynamical GENIE3 for the inference of gene networks from time series expression data
In this paper, the authors are working on several time course gene expression datasets, including &quot;Drosophila melanogaster embryogenesis&quot; dataset (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE6186) . This dataset has the whole genome ( 14064 genes) of Drosophila melanogaster measured over 31 time-points.
In the dynGenie3 paper, we analyse a subset of these  14064 genes, as they write:
&quot;We focused our analysis on the 1000 genes whose expression vary the most across the time series.&quot;
I want to know how do we measure the variance in expression across time series? What statistical tests might have been performed? I couldn't find any more information in the paper so I am assuming it might be something simple and frequently done.  Need some hints.
Maybe my thoughts are too simple, but wouldn't the computation of the variance per gene suffice for this? You really do not need a statistical test, since they are not talking about DEGs, just high-variant genes.