Sonia Nan Kim

The paper uses somatic mutations to analyze lineage divergence in human cortical regions, finding late divergence of neuronal cell types and regional inhomogeneities in progenitor proliferation.

DeepMosaic detects mosaic single nucleotide variants without control samples using deep convolutional neural networks, achieving high accuracy and uncovering many variants missed by existing methods.

The paper evaluates brain somatic mosaicism in the adult human to identify rules governing cellular distribution during embryogenesis.

The paper introduces a machine learning method to detect somatic L1 insertions in human brain tissue, revealing their widespread distribution in neurons and glia and potential role in neuropsychiatric diseases.

PRDD-seq simultaneously reconstructs cell type, lineage, and birthdate in human brain tissue by analyzing RNA and DNA mutations in single cells.

The paper analyzes somatic mutations in autistic and control brains, finding higher mutation rates in ASD brains, particularly in enhancer regions.