BACKGROUND Machine learning (ML) algorithms and methods offer great tools to analyze large complex genomic datasets. Our goal was to compare the genomic architecture of schizophrenia (SCZ) and autism spectrum disorder (ASD) using ML. METHODS In this paper, we used regularized gradient boosted machines to analyze whole-exome sequencing (WES) data from individuals SCZ and ASD in order to identify important distinguishing genetic features. We further demonstrated a method of gene clustering to highlight which subsets of genes identified by the ML algorithm are mutated concurrently in affected individuals and are central to each disease (i.e., ASD vs. SCZ "hub" genes). RESULTS In summary, after correcting for population structure, we found that SCZ and ASD cases could be successfully separated based on genetic information, with 86-88% accuracy on the testing dataset. Through bioinformatic analysis, we explored if combinations of genes concurrently mutated in patients with the same condition ("hub" genes) belong to specific pathways. Several themes were found to be associated with ASD, including calcium ion transmembrane transport, immune system/inflammation, synapse organization, and retinoid metabolic process. Moreover, ion transmembrane transport, neurotransmitter transport, and microtubule/cytoskeleton processes were highlighted for SCZ. CONCLUSIONS Our manuscript introduces a novel comparative approach for studying the genetic architecture of genetically related diseases with complex inheritance and highlights genetic similarities and differences between ASD and SCZ.

中文翻译：

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外显子组三重奏的机器学习分析，以对比自闭症和精神分裂症的基因组结构。


背景技术机器学习（ML）算法和方法提供了分析大型复杂基因组数据集的强大工具。我们的目标是使用机器学习比较精神分裂症 (SCZ) 和自闭症谱系障碍 (ASD) 的基因组结构。方法在本文中，我们使用正则化梯度增强机器来分析来自 SCZ 和 ASD 个体的全外显子组测序 (WES) 数据，以识别重要的区分遗传特征。我们进一步演示了一种基因聚类方法，以突出显示 ML 算法识别的哪些基因子集在受影响的个体中同时发生突变，并且是每种疾病的核心（即 ASD 与 SCZ“中心”基因）。结果总而言之，在校正群体结构后，我们发现可以根据遗传信息成功区分 SCZ 和 ASD 病例，在测试数据集上的准确度为 86-88%。通过生物信息学分析，我们探讨了具有相同病症的患者中同时突变的基因组合（“中心”基因）是否属于特定途径。研究发现几个主题与 ASD 相关，包括钙离子跨膜转运、免疫系统/炎症、突触组织和类视黄醇代谢过程。此外，SCZ 还强调了离子跨膜运输、神经递质运输和微管/细胞骨架过程。结论 我们的手稿介绍了一种新颖的比较方法，用于研究具有复杂遗传的遗传相关疾病的遗传结构，并强调了 ASD 和 SCZ 之间的遗传相似性和差异。