Yes, thanks for being selective! I appreciated the author's relatively minor discussion of the disease data and more expansive discussion of the rest. For compl

Yes, thanks for being selective! I appreciated the author's relatively minor discussion of the disease data and more expansive discussion of the rest. For completeness: when I say 'GWAS' in this context I am referring to 'common SNPs' (MAF>=5%, or perhaps down to 1%), not to genome-wide association studies based on the SNPs. I used to argue with my labmates about the proper use of the term 'GWAS': I felt that it should refer to the studies only, and 'common SNPs' should be called 'common SNPs'; my labmates preferred to call common SNPs 'GWAS data' and I've finally been converted. Anyways, I do think that expression+GWAS is useful, but it's not going to get us to a place that's better than history for most diseases.[1] Exome and then genome sequencing will be needed for that. [1] = On the other hand, Purcell has an interesting paper out that discards the genome-wide significance threshold, with interesting results.