7.2 years ago by
South San Francisco, CA
To add a little bit of detail to UnivStudent's answer:
Personally I find the lumi package to have less flexibility than beadarray. If you are new to microarray analysis in R, the limma user guide is a must read. How you should think of microarray analysis is that there are certain platform specific methods used (covered by beadarray/lumi/limma) and the underlying analysis is typically the same.
One of the platform specific methods is background correction. I've used neqc() in limma to great success. ref
Now your question of probe-based vs transcript-based gets to one of the differences between Affymetrix and Illumina arrays. Typically with Illumina arrays you stick with probes since each probe 'usually' corresponds to a gene (1 probe per gene) rather than summarizing across probes (several probes per gene). However, some tools (such as IPA and partek) will gene-summarize (combine multiple probes -> gene using mean/median/etc) but this will not change the vast majority of gene expression values.
Lastly, be aware of terminology, with Illumina microarrays you will sometimes find the term bead-summarized. This has to do with the technology (multiple identical probes are put onto different beads) and this bead-summarized value will usually be value you get from the facility running the microarray and the one you use for differential expression analysis. More advanced analysis using raw bead values can be done using beadarray.