Analysis of variance (ANOVA) was used as statistical procedure to reveal the significance (F and p-values) and the effect size (eta-squared) of the various sources of variations considered in the study.
We first estimate the various sources of variations in an experiment and if microarray data have been properly normalized, there should be no systematic biases among estimated values of genes.
Our statistical model incorporates various sources of variations that generate probabilistic characterization of such an association.
This generalized measure of agreement takes into various sources of variation.
Turnover and post-transcriptional regulations of mRNAs probably also depend on various sources of variation, further attenuating the correlation between chromatin and transcript levels differences.
Ratiometric data analysis minimizes various sources of variation related to the construction and hybridization of the microarrays, thus providing the highest level of precision in the comparison of gene expression profiles from two different RNA samples [ 2].
The aim of this study was to explore the contributions of various sources of variation, such as population structure, SNP variants, and gene expression levels, to a set of growth related traits (body weight, feed intake, and feed efficiency) in mice.
In addition, we highlighted various sources of experimental variations in studies involving microarray gene expression, real-time polymerase chain reaction, proteomics, and other bioinformatics technologies.
To investigate this further, we need studies in which the various sources of phenotypic variation can be partitioned to discern the relationship between additive genetic variation of particular traits of interest and fitness (Lande and Arnold 1983; Etterson 2004a) and document genetic variances and covariances under a range of conditions (Etterson 2004b).
This striking pattern of results, holding for various sources of exogenous variation in skills and across different contexts, yields important implications for policy.
More generally, it is crucial to build networks in a manner that realistically takes into account various sources of expression variation (transcription factors activities, alternative splicing, post-translational modifications of proteins, etc).. Thus, other elements shall be considered in a network structure, and extensions are in progress.
