Aging is broadly defined as a time-dependent progressive decline in the functional and physiological integrity of
organisms. Previous studies and evolutionary theories of aging suggest that aging is not a programmed process
but reflects dynamic stochastic events. In this study, we test whether transcriptional noise shows an increase
with age, which would be expected from stochastic theories. Using human brain transcriptome dataset, we
analyzed the heterogeneity in the transcriptome for individual genes and functional pathways, employing
different analysis methods and pre-processing steps. We show that unlike expression level changes, changes in
heterogeneity are highly dependent on the methodology and the underlying assumptions. Although the
particular set of genes that can be characterized as differentially variable is highly dependent on the methods,
we observe a consistent increase in heterogeneity at every level, independent of the method. In particular, we
demonstrate a weak but reproducible transcriptome-wide shift towards an increase in heterogeneity, with
twice as many genes significantly increasing as opposed to decreasing their heterogeneity. Furthermore, this
pattern of increasing heterogeneity is not specific but is associated with a wide range of pathways
