Geetha Senthil

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.

This paper performs a large-scale eQTL meta-analysis across cerebral cortical and cerebellar brain regions, identifying distinct eQTL patterns and demonstrating improved power over existing studies.

The paper functionally annotates rare structural variants in the human brain by integrating SV calling with RNA-seq data to assess their regulatory effects and prioritize pathogenic deletions.