Craig L. Bohrson

The paper compares somatic mutation rates in neurons and oligodendrocytes across aging human brains, finding faster mutation accumulation in oligodendrocytes and distinct genomic distribution patterns.

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 PTA for single-cell DNA sequencing and SCAN2 to detect somatic SNVs and indels in single neurons, finding age-related increases in both with indels having greater functional impact.

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.

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

The paper introduces LiRA, a method to distinguish true mutations from artifacts in single-cell DNA sequencing data by phasing somatic variants with germline variants.

The paper identifies age-related accumulation of somatic mutations in human neurons and links them to neurodegenerative diseases.