Fig. 1: Summary of disease informativeness of allelic-effect deep learning annotations. | Nature Communications

Fig. 1: Summary of disease informativeness of allelic-effect deep learning annotations.

From: Evaluating the informativeness of deep learning annotations for human complex diseases

Fig. 1

We report the number of allelic-effect annotations with significant heritability enrichment, marginal conditional Ļ„ā‹†, and joint conditional Ļ„ā‹†, across a different deep learning models (DeepSEA/Basenji), b different aggregation strategies (Avg/Max) and c different chromatin marks (DNase/H3K27ac/H3K4me1/H3K4me3). Numerical results are reported in Supplementary Table 5 (numerical summary of results), Supplementary Table 6 (enrichment and marginal Ļ„ā‹† for all tissues, all traits analysis), Supplementary Table 15 (enrichment and marginal Ļ„ā‹† of blood cell types, blood traits analysis), Supplementary Table 21 (enrichment and marginal Ļ„ā‹† of brain tissues, brain traits analysis) and Supplementary Table 27 (joint Ļ„ā‹† of brain tissues, brain traits analysis). No Supplementary Table is needed for joint Ļ„ā‹† of all tissues, all traits (1 marginally significant annotation) or blood cell types, blood traits (0 marginally significant annotations).

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