Hello Bioconductor forum,
I used Bioconductor package limma for analysis of differentially expressed genes in this Agilent microarray dataset available under https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=+GSE59408.
Now my question is: are there any alternative packages to limma for analysis of differentially expressed genes in 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.
Kind regards,
Max


By my understanding, the alternatives to limma for RNA-seq, such as edgeR and DESeq, were created because limma's statistical model was not (at that time) a good fit for count data. Do you have concerns about limma's statistical model for your data, or is there a specific statistical method you're looking to apply and you're hoping to find a package to do it?
Hello Ryan,
thank you for your answer. No, I don't have concerns about limma' statistical model for my data, the results for the DEGs with limma are in accord with the gene expression described in the original publication Prediction of antibiotic resistance by gene expression profiles available under https://www.nature.com/articles/ncomms6792.
However, the analysis with limma revealed some additional, possibly interesting genes in this dataset and I thought about using a different package/software/method to see if these results are reproducible.