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Fig. 4 | Human Genomics

Fig. 4

From: Novel clinical, molecular and bioinformatics insights into the genetic background of autism

Fig. 4

Visualization of risk model results for 33 ASD patients (18 non-severe and 15 severe) using the 26 variants selected during LOOCV. The dendrogram was obtained by performing hierarchical clustering (using Euclidean distance and average linkage algorithm) of model prediction outputs. The clustering represents the molecular subtypes obtained by the trained model for all ASD patients. The two molecular subtypes as predicated by the risk models are color-coded as pink for the most severe cases (high-risk individuals), light green for least severe cases (low-risk individuals). Moreover, the continuous spectrum of risk prediction scores is shown in the red-green gradient traversing the dendrogram. Patients are further sorted by severity in descending order. Clinical experimental data is also viewed in parallel to the results obtained from the machine learning algorithm and are shown as columns with dark and light gray boxes. The boxes denote the different level of severity for the six different clinical data available for this study. The molecular classification of samples 8574_9, 8574_14, 8574_7 and 8574_23 appears to differ from the clinical classification. These samples cluster separately from the rest of the samples with similar severe clinical phenotypes. Similarly, based on theory molecular classification, samples 8574_13 and 8574_18 also appear to cluster away from samples of similar non-severe clinical classification

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