Abstract:
:The principles embodied by the Developmental Origins of Health and Disease (DOHaD) view of 'life history' trajectory are increasingly underpinned by biological data arising from molecular-based epigenomic and transcriptomic studies. Although a number of 'omic' platforms are now routinely and widely used in biology and medicine, data generation is frequently confounded by a frequency distribution in the measurement error (an inherent feature of the chemistry and physics of the measurement process), which adversely affect the accuracy of estimation and thus, the inference of relationships to other biological measures such as phenotype. Based on empirical derived data, we have previously derived a probability density function to capture such errors and thus improve the confidence of estimation and inference based on such data. Here we use published open source data sets to calculate parameter values relevant to the most widely used epigenomic and transcriptomic technologies Then by using our own data sets, we illustrate the benefits of this approach by specific application, to measurement of DNA methylation in this instance, in cases where levels of methylation at specific genomic sites represents either (1) a response variable or (2) an independent variable. Further, we extend this formulation to consideration of the 'bivariate' case, in which the co-dependency of methylation levels at two distinct genomic sites is tested for biological significance. These tools not only allow greater accuracy of measurement and improved confidence of functional inference, but in the case of epigenomic data at least, also reveal otherwise cryptic information.
journal_name
J Dev Orig Health Disjournal_title
Journal of developmental origins of health and diseaseauthors
Pleasants AB,Wake GC,Shorten PR,Hassell-Sweatman CZ,McLean CA,Holbrook JD,Gluckman PD,Sheppard AMdoi
10.1017/S2040174414000476subject
Has Abstractpub_date
2015-02-01 00:00:00pages
17-26issue
1eissn
2040-1744issn
2040-1752pii
S2040174414000476journal_volume
6pub_type
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