Now my question is: are there any alternative packages to limma for analysis of differentially expressed genesin microarray datasets? I would like to compare results for the differentially expressed genes I found with limma. I did some research but only found alternative packages to limma for RNA-seq data and not for microarray data.
personally i would not consider anything better than limma for the analysis of microarray data (not only-)-this has been proven in numerous scientific published papers and pipelines-rather than your approach of using alternative R packages, you could focus on the interpretation of your DE list. Does functional enrichment of your DE genes provides "sensible results" regarding your biological question ? Or for instance, have you performed any literature mining to search for any similar transcriptomic analyses that have answered "similar experimental designs ? Also in parallel, you could create some additional plots, like a heatmap to inspect the expression pattern of your DE genes (and lots of more...)
Nevertheless, i could for instance mention the samr R package and cyberT test as alternatives, but i clearly think that limma provides the best choise.
if you are interested in two group comparisons only, the st CRAN package implements various alternative variance shrinkage estimators, the CAT score even takes correlations between the genes into account: