The orthogonal arrays in the design of experimental method proposed by Taguchi were adopted to conduct the multiple-factor experiment.
The general linear models capability (glm EdgeR) was used to account for the multiple factors in the experiment (i.e. colony, developmental stage and irradiation treatment).
These approaches have provided valuable information, but frequently have multiple factors changing throughout the experiment, and the mycobacteria often fail to grow and metabolize.
Then, the functions estimateGLMTrendedDisp and estimateGLMTagwiseDisp were used to estimate genewise dispersion allowing a possible trend with average count size as recommended for experiments with multiple factors.
The two-factor ANOVA used in this study to determine the influence of AtNHX1 is considered a powerful tool for the analysis of microarray experiments with multiple factors [ 11], as it utilized all 48 microarray data points to distinguish between an effect of genotypes across all treatments (main effect) and a treatment-dependent effect of lines (genotype × treatment interaction).
A similar hypothesis could be advanced to include Rev1, along with hPol ι and hPol κ, on the basis of the present experiments, although multiple factors will affect bypass at the replication fork (e.g., the amounts of the various bypass polymerases in a cell, relative catalytic activities, and their propensity for interaction with ancillary replication machinery, such as PCNA).
The algorithm of edgeR fits a negative binomial model to the count data, estimates dispersion, and measures differences using the generalized linear model likelihood ratio test which is recommended for experiments with multiple factors, such as the simultaneous analysis of age and diet in our study.
The algorithm of edgeR fits a negative binomial model to the count data, estimates dispersion, and measures differences using the generalized linear model likelihood ratio test which is recommended for experiments with multiple factors, such as the simultaneous analysis of the effects of age and diet in our study.
In our experience, multiple factors can affect attachment including Matrigel and conditioned media used at the time of each experiment.
Future work will expand on this proof-of-principle experiment using multiple factors over a range of concentrations.
