Table 8.
Testing for genetic overlap with Doust al. and Wang et al. on reading/language phenotypes, based on gene-based test statistics
| (1) GWAS by Doust et al. | |||||||
|---|---|---|---|---|---|---|---|
| Phenotype | P < 0.05 | P < 0.01 | P < 0.001 | P < 1e-04 | P < 1e-05 | P < 1e-06 | Aggregate_P |
| CCR_Total | 8.73E-02 | 4.18E-02 | 2.98E-02 | 1.47E-02 | 8.63E-03 | 2.74E-02 | 4.40E-02 |
| CDICT_Total | 1.88E-02 | 9.01E-03 | 6.69E-02 | 4.56E-02 | 2.68E-02 | 1.73E-02 | 3.76E-02 |
| CVB_Total | 6.60E-04 | 3.16E-04 | 1.97E-01 | 9.68E-02 | 5.70E-02 | 3.67E-02 | 1.90E-03 |
| CVD_Total | 1.22E-04 | 1.12E-01 | 4.76E-02 | 4.54E-01 | 4.39E-01 | 2.83E-01 | 7.31E-04 |
| CVK_Total | 6.81E-04 | 7.73E-02 | 6.58E-02 | 6.15E-01 | 7.24E-01 | 4.66E-01 | 4.09E-03 |
| DS_Total | 2.03E-01 | 1.94E-01 | 8.26E-02 | 4.06E-02 | 2.39E-02 | 1.54E-02 | 7.18E-02 |
| EVB_Total | 2.69E-02 | 1.29E-02 | 5.78E-01 | 2.84E-01 | 2.23E-01 | 1.56E-01 | 7.73E-02 |
| MS_Total | 8.41E-04 | 4.03E-04 | 5.66E-01 | 4.00E-01 | 2.42E-01 | 1.56E-01 | 2.42E-03 |
| PairC_Total | 6.51E-02 | 3.12E-02 | 2.65E-02 | 1.41E-01 | 1.20E-01 | 7.74E-02 | 9.36E-02 |
| WO_Total | 4.49E-02 | 2.15E-02 | 1.45E-01 | 4.23E-01 | 2.73E-01 | 3.05E-01 | 1.29E-01 |
| (2) GWAS by Wang et al. | |||||||
| Phenotype | P < 1e-05 | ||||||
| CLD_Total | 4.89E-03 | ||||||
| CVK_Total | 8.15E-03 | ||||||
| EMA_Total | 8.44E-03 | ||||||
| CVB_Total | 1.26E-02 | ||||||
| MS_Total | 1.52E-02 | ||||||
| RC_OE | 4.75E-02 | ||||||
The above is based on the Simes test. Only traits showing significant results across at least two p-value thresholds (for the first study) and or at p < 1e-5 (for the second study) are shown. Full results (including results from Simes and ACAT tests) are presented in Supplementary Data 14.
For gene-set analysis based on the GWAS by Wang et al., since the number of genes with available data is small, we aggregated the top genes across all eight phenotypes studied by Wang et al.
For details of the statistical test, please refer to the main text. Briefly, we first extracted top genes from the external datasets with (gene-based) p-values smaller than predefined cutoffs, then extracted the same set of genes from our sample. We then tested whether the gene-set (as a whole) was significantly associated with the studied phenotypes. This replication analysis was conducted under various p-value cutoffs (p = 0.05, 1e-2, 1e-3, 1e-4, 1e-5 and 1e-6) (for the Doust et al. study). For the other GWAS, only one threshold was used, as only the summary gene-based statistics with p < 1e-5 were available.