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Xin He

Researcher at University of Chicago

Publications -  96
Citations -  6591

Xin He is an academic researcher from University of Chicago. The author has contributed to research in topics: Gene & Biology. The author has an hindex of 29, co-authored 78 publications receiving 4548 citations. Previous affiliations of Xin He include University of Hong Kong & University of California, San Francisco.

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Journal ArticleDOI

Insights into Autism Spectrum Disorder Genomic Architecture and Biology from 71 Risk Loci.

TL;DR: Analysis of de novo CNVs from the full Simons Simplex Collection replicates prior findings of strong association with autism spectrum disorders (ASDs) and confirms six risk loci, including 6 CNV regions.
Journal ArticleDOI

Large-Scale Exome Sequencing Study Implicates Both Developmental and Functional Changes in the Neurobiology of Autism

F. Kyle Satterstrom, +201 more
- 06 Feb 2020 - 
TL;DR: The largest exome sequencing study of autism spectrum disorder (ASD) to date, using an enhanced analytical framework to integrate de novo and case-control rare variation, identifies 102 risk genes at a false discovery rate of 0.1 or less, consistent with multiple paths to an excitatory-inhibitory imbalance underlying ASD.
Journal ArticleDOI

Large-Scale Exome Sequencing Study Implicates Both Developmental and Functional Changes in the Neurobiology of Autism

F. Kyle Satterstrom, +153 more
TL;DR: Using an enhanced Bayesian framework to integrate de novo and case-control rare variation, 102 risk genes are identified at a false discovery rate of ≤ 0.1, consistent with multiple paths to an excitatory/inhibitory imbalance underlying ASD.
Journal ArticleDOI

Integrated Model of De Novo and Inherited Genetic Variants Yields Greater Power to Identify Risk Genes

TL;DR: TADA's integration of various kinds of WES data can be a highly effective means of identifying novel risk genes and validated TADA using realistic simulations mimicking rare, large-effect mutations affecting risk for ASD and show it has dramatically better power than other common methods of analysis.