Table 1.
Statistical analysis
| Data set | Statistical test | Main effect | Post hoc comparisonsa |
|---|---|---|---|
| Figure 2B | Kruskal–Wallis test followed by FDR tests | H = 10.37, P = 0.0157 | CON versus EE: P = 0.4815 CON versus ER: P = 0.4815 CON versus SI: P = 0.0146 EE versus ER: P = 0.4815 EE versus SI: P = 0.0146 ER versus SI: P = 0.0823 |
| Figure 2C | Kruskal–Wallis test followed by FDR tests | H = 16.16, P = 0.0011 | CON versus EE: P = 0.0015 CON versus ER: P = 0.0820 CON versus SI: P = 0.6455 EE versus ER: P = 0.1237 EE versus SI: P = 0.0016 ER versus SI: P = 0.0841 |
| Figure 2D | One-way ANOVA followed by Sídák tests | F(3,34) = 10.59, P < 0.0001 | CON versus EE: P < 0.0001 CON versus ER: P = 0.0139 CON versus SI: P = 0.3469 EE versus ER: P = 0.4924 EE versus SI: P = 0.0095 ER versus SI: P = 0.5447 |
| Figure 2E | One-way ANOVA followed by Sídák tests | F(3,34) = 5.49, P < 0.0035 | CON versus EE: P = 0.0140 CON versus ER: P = 0.5857 CON versus SI: P = 0.9504 EE versus ER: P = 0.6296 EE versus SI: P = 0.0043 ER versus SI: P = 0.2386 |
| Figure 2G | Kruskal–Wallis test followed by FDR tests | H = 18.73, P = 0.0003 | CON versus EE: P = 0.0094 CON versus ER: P = 0.1687 CON versus SI: P = 0.0094 EE versus ER: P = 0.0080 EE versus SI: P < 0.0001 ER versus SI: P = 0.0837 |
| Figure 2H | Kruskal–Wallis test followed by FDR tests | H = 19.37, P = 0.0002 | CON versus EE: P = 0.0018 CON versus ER: P = 0.0098 CON versus SI: P = 0.1211 EE versus ER: P = 0.1836 EE versus SI: P = 0.0004 ER versus SI: P = 0.0018 |
| Figure 3B | Kruskal–Wallis test followed by FDR tests | H = 18.69, P = 0.0003 | CON versus EE: P = 0.0068 CON versus ER: P = 0.0791 CON versus SI: P = 0.0405 EE versus ER: P = 0.1700 EE versus SI: P = 0.0002 ER versus SI: P = 0.0053 |
| Figure 3C | Kruskal–Wallis test followed by FDR tests | H = 4.166, P = 0.2441 | CON versus EE: P = 0.7352 CON versus ER: P = 0.2458 CON versus SI: P = 0.7352 EE versus ER: P = 0.5544 EE versus SI: P = 0.7352 ER versus SI: P = 0.2458 |
| Figure 3E | Kruskal–Wallis test followed by FDR tests | H = 20.62, P = 0.0001 | CON versus EE: P < 0.0001 CON versus ER: P = 0.0046 CON versus SI: P = 0.0465 EE versus ER: P = 0.1561 EE versus SI: P = 0.0142 ER versus SI: P = 0.1211 |
| Figure 4B | One-way ANOVA followed by Sídák tests | F(2,19) = 37.78, P < 0.0001 | EE versus ER: P = 0.0064 EE versus SI: P < 0.0001 ER versus SI: P = 0.0006 |
| Figure 4C | One-way ANOVA followed by Sídák tests | F(2,19) = 16.06, P < 0.0001 | EE versus ER: P = 0.9997 EE versus SI: P = 0.0004 ER versus SI: P = 0.0005 |
| Figure 4E | One-way ANOVA followed by Sídák tests | F(2,19) = 13.41, P = 0.0002 | EE versus ER: P = 0.9920 EE versus SI: P = 0.0009 ER versus SI: P = 0.0016 |
| Figure 4F | One-way ANOVA followed by Sídák tests | F(2,19) = 77.14, P < 0.0001 | EE versus ER: P = 0.7856 EE versus SI: P < 0.0001 ER versus SI: P < 0.0001 |
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aP-values for post hoc comparisons after Kruskal–Wallis are adjusted to account for multiple comparisons
