Machine Learning-Derived Subtypes of Autism Reveal Distinct Genetic Contributions from Common and Rare Variants

Qing Tan, Jingyu Xie, LeeAnne Green Snyder, Runpu Chen, Le Yang, Fei Chen, Brett Trost, Bridget Fernandez, Charleston Wen-Kai Chiang, Nicholas Mancuso, Chang April Shu

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DOI: 10.64898/2026.10.19.26365670
Published: 2026-10-24
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Publisher: openRxiv
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Cite this work

BibTeX

@article{allodium:10.64898/2026.10.19.26365670,
  title = {Machine Learning-Derived Subtypes of Autism Reveal Distinct Genetic Contributions from Common and Rare Variants},
  author = {Qing Tan and Jingyu Xie and LeeAnne Green Snyder and Runpu Chen and Le Yang and Fei Chen and Brett Trost and Bridget Fernandez and Charleston Wen-Kai Chiang and Nicholas Mancuso and Chang April Shu},
  year = {2026},
  doi = {10.64898/2026.10.19.26365670},
  url = {https://doi.org/10.64898/2026.10.19.26365670}
}

RIS

TY  - JOUR
TI  - Machine Learning-Derived Subtypes of Autism Reveal Distinct Genetic Contributions from Common and Rare Variants
AU  - Qing Tan
AU  - Jingyu Xie
AU  - LeeAnne Green Snyder
AU  - Runpu Chen
AU  - Le Yang
AU  - Fei Chen
AU  - Brett Trost
AU  - Bridget Fernandez
AU  - Charleston Wen-Kai Chiang
AU  - Nicholas Mancuso
AU  - Chang April Shu
PY  - 2026
DO  - 10.64898/2026.10.19.26365670
UR  - https://doi.org/10.64898/2026.10.19.26365670
ER  -

APA

Tan, Q., Xie, J., Snyder, L. G., Chen, R., Yang, L., Chen, F., Trost, B., Fernandez, B., Chiang, C. W., Mancuso, N., & Shu, C. A. (2026). Machine Learning-Derived Subtypes of Autism Reveal Distinct Genetic Contributions from Common and Rare Variants. https://doi.org/10.64898/2026.10.19.26365670

Source records

crossref · retrieved 2026-11-09T18:55:26.792Z