Kevin P. White

The paper identifies eQTLs, rQTLs, and pQTLs in the human brain and shows that many eQTL effects are attenuated post-transcriptionally, yet still correlate with schizophrenia GWAS signals.

The paper processes single-nuclei multi-omics data from 388 human brains to identify regulatory elements and build cell-type networks, revealing changes in aging and neuropsychiatric disorders.

The paper identifies and validates enhancer regions in primary human neural progenitor cells using capture STARR-seq, linking them to genes involved in psychiatric disease pathways.

The paper presents a catalog of transcription factor binding sites in Drosophila and C. elegans, revealing tissue-specific regulatory relationships using machine learning.

The paper analyzes whole-genome data from Nigerian breast cancer patients, identifying ethnic-driven somatic evolution and distinct genomic subtypes associated with African ancestry.

This study compares mock IP and DNA input controls in ChIP-seq, showing that mock IP better removes spurious sites, while DNA input has unique advantages, and proposes combining both for improved binding site detection.

The paper introduces STARRPeaker, a processing pipeline for STARR-seq data that improves enhancer detection by addressing sequencing biases and RNA stability effects.

The paper develops a custom ENCODE annotation for cancer genomics, highlighting TF-RBP interactions and network rewiring during oncogenesis, and validates findings using experimental assays.

DRAMS detects and corrects sample mix-ups in multi-omics data by aligning genetic and omics data, improving statistical power and result quality.

The paper evaluates chromatin accessibility in prefrontal cortex samples from schizophrenia cases and controls, finding high heritability enrichment in open chromatin regions but no differential accessibility between groups.