Extended Data Fig. 7 |. Out-of-sample replication of ASD subgroup clinical symptoms and atypical connectivity in NDA dataset (N_NDA = 85 ASD subjects).

We repeated the main analyses to define ASD subgroups using the NDA dataset (RCCA and clustering). This analysis replicated key results from ABIDE, such that the four NDA subgroups (N_{NDA_1} = 20, N_{NDA_2} = 21; N_{NDA_3} = 27; N_{NDA_4} = 17) exhibited clinical symptom / behavior profiles and atypical connectivity patterns that were highly similar to those observed in the ABIDE subgroups (N_{ABIDE_4} = 69, N_{ABIDE_2} = 87; N_{ABIDE_3} = 67; N_{ABIDE_4} = 76). In this summary figure, we plot the clinical symptom scores (NDA: a-d, ABIDE: i-l; boxplots as in Extended Data Fig. 5) and atypical connectivity patterns for each subgroup (NDA: e-h, ABIDE: m-p). As expected, statistical power to detect significant atypical connectivity was reduced due to the smaller sample size of NDA. Here, the heatmaps show atypical functional connectivity in NDA and ABIDE subgroups, with the NDA subgroups thresholded by significance from ABIDE for comparison (that is, we set elements in the NDA heatmaps with FDR < 0.05 from a connectivity (two-sided Welch’s t-test in ABIDE heatmaps to 0). However, we confirmed that compared to an empirical null (100 shuffles, see Methods for details), atypical connectivity patterns in the NDA ASD subgroups were more correlated with ABIDE ASD subgroups than expected by chance (P₁ = 0.0099, P₂ = 0.0297, P₃ = 0.0099, P₄ = 0.0198). Note that the P values correspond to the probability of obtaining the observed sum of ranks statistic (sum of observed ranks across a range of FDR thresholds, FDR in {1, 0.05, 0.01, 0.005, 0.001, 0.0005, 0.0001, 0.00005}) under the empirical null. For additional results, see Supplementary Fig. 21.