Reenal Pattni

This study identifies C4 protein expression in neutrophils and monocytes in schizophrenia, linking it to C4A gene copy number only in patients.

This study uses single-cell whole genome amplification to link somatic mutations to cell identity and ancestry in a live donor.

This study develops a 'Stress-in-a-dish' model using cortical organoids to investigate the molecular effects of cortisol on gene expression and potential PTSD-related mechanisms.

The paper develops a method to detect complex structural variants across human genomes and finds they are associated with phenotypic hotspots and evolutionary changes.

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

This study identifies somatic SNVs in non-cancerous human brain tissues and establishes best practices for detecting low-frequency variants.

This study examines the transcriptome and epigenome effects of the 15q13.3 microdeletion in human induced neurons, identifying gene expression and pathway changes linked to neuropsychiatric disorders.

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 introduces CTLR-Seq, a method to resolve complex genomic regions with high accuracy, and applies it to study CNVs associated with schizophrenia and autism.

The paper investigates the molecular effects of 16p11.2 CNVs on gene expression and DNA methylation using an iPSC-to-iN model and identifies potential contributing genes.

The paper provides a comprehensive whole-genome analysis of K562, identifying genomic structural features and their impact on functional genomics data.

This paper provides a haplotype-resolved genome analysis of the HepG2 cell line, identifying genomic features and allele-specific regulation to support functional genomics studies.

The paper generates deep re-sequencing datasets for the Venter/HuRef genome to develop and benchmark genome analysis tools using Illumina sequencing.

The paper compares low-coverage whole-genome sequencing strategies to array-based methods for detecting copy number variations, finding WGS more efficient and accurate.