Abstract
A parametric intellectual framework* for the analysis of transcriptome data is demonstrated to yield coincident results when applied to data acquired using various microarray platforms. Microarrays are widely employed to acquire transcriptome information, and several platforms of chips are currently in use. However, discrepancies among studies are frequently reported, casting doubt on the reliability. The inconsistency among observations can be largely attributed to differences among the analytical frameworks employed for data analysis. The existing frameworks are based on different philosophies often based on ad hoc styles, and yield different results. Here, a parametric framework based on a statistic model that bases on thermodynamic model of transcriptome formation. The framework is tested in data acquired using several slide-glass-type chips and GeneChip. The expressional changes observed and genes selected are coincident between platforms, achieving superior universality of data compared to other frameworks.
*assumptions, theories and ideas on which we can think
