One strategy involves identifying genes which show main effects and then compositing only these to then test an interaction with some environmental parameter (e.g., Docherty, Kovas, & Plomin, 2011).
Matrix and polymerase viral genes, which show a low rate of variation, were chosen to design amplification assays to ensure that any genotype of the human metapneumovirus could be detected.
However, there are other genes which show only an association.
Pearson's correlation test was used for the correlations between the expressions of all three genes, which show normal distribution.
Expression of at least two genes which show significantly different expression between mutant and WT animals may also be affected by background strain.
It has previously been shown that several LexA independent genes are regulated within a twofold range [3], with exceptions like the nrdB and nrdA genes, which show regulation beyond the twofold range [44].
In summary, we presented a machine learning based approach to predict the co-expression patterns of the human intronic miRNAs and their host genes, which show a high accuracy and validation and could be further extended to other species.
Analysis of potential horizontal gene transfer (HGT) events in M1 identified a number of genes which show high sequence similarity to non-methanogens, typically from members of the bacterial phylum Firmicutes (Table S2).
These analyses only use genes which show significant changes in gene expression in order to reduce unrelated variation attributable to genes which do not show significant responses to these experimental treatments.
Research efforts have focused recently on methylation of human genes which show promise as diagnostic classifiers.
We were particularly interested in genes which show a synergistic dependence on AtxA and CO2.
