@Chris Ponting, as arnoble says, can you clarify, was the tissue enrichment based on putting those 13 genes into a discrete gene set and seeing if those 13 genes specifically, without regard for their actual p-values/z-scores, were enriched among all genes expressed in a tissue?
Or was every one of the ~18,000 genes' z-scores considered in the enrichment in a continuous manner (where if genes with high z-scores, which includes, but is not limited to, those top 13, have high expression, and genes with low z-scores have low expression, then the genes are considered to be enriched in the tissue)?
Figure 3 says this was a "MAGMA gene-tissue analysis". Looking at the cited MAGMA paper, the only equations I see for their gene-set analyses have Z as the dependent variable in a linear regression. With Z being:
To perform the gene-set analysis, for each gene g the gene p-value pg computed with the gene analysis is converted to a Z-value Zg = Φ−1(1 – pg), where Φ−1 is the probit function.
Edit: The paper says it used the
FUMA platform. FUMA includes MAGMA, so I assume that's where the MAGMA analysis is done. The documentation details the method for tissue analysis, which looks like it uses the z-score for every gene.