I would like to compare data between experiments that use different RNA technologies. I have RNAseq data from Illumina, and there is a vast availability of Micro array data available from collaborators and publicly. Can anyone point me to some reviews or information regarding how to pool these two different types of data, what the caveats are, and how to do it in a logical manner?
I would look at how microarrays are compared between labs and between species, since there is a long history of trying to compare DE between experiments.
The easiest is the rank approach, of course now you have to decide whether to use the probeset genes or something bigger.
Raw aggregation methods combine the expression data for a gene from each microarray experiment, and then evaluate the significance of the combined expression data. Error variables can be included to account for global systematic differences between different experiments, and also for noise within each experiment. Choi et al. (2003) developed such an aggregation method, termed a t-based approach, and applied it to various cancer datasets. They demonstrated that slight but consistent expression changes could be identified for some genes, which no one microarray study alone could identify as significant. Rank-based methods sort the genes in each study according to the significance of differential expression and then aggregate the rankings of each gene across studies, which allow to overcome differences in P-value comparisons. Permutation tests can then be used to identify genes whose aggregated rankings are significant. Finally, P-value aggregation methods combine the P-values for each gene's expression obtained from different microarray experiments, to obtain an aggregate P-value. P-values for a gene can be aggregated by various methods, e.g. by taking the minimum or the product of the P-values.
I highly recommend this review article that discuss about your question and provide some directions.
Microarrays, deep sequencing and the true measure of the transcriptome (OA)
Figure 3 from the article: Comparison of array and RNA-Seq data for measuring differential gene expression in the heads of male and female D. pseudoobscura.
