Extended Data Fig. 2: Performance of all tested models on cross-gene prediction.
From: Personal transcriptome variation is poorly explained by current genomic deep learning models
Cross-gene performance for (a) Enformer, (b) Basenji2, (c) ExPecto, and (d) Xpresso. For a given individual, cross-gene performance is defined as the correlation between their measured gene expression levels and gene expression predictions obtained using their personalized genome sequences. Correlations were computed across the 3,259 genes with at least one statistically signficant (FDR < 5%) eQTL in the Geuvadis analysis. Each histogram displays the distribution of cross-gene performance over all individuals.
