David Zhang

The paper shows that sequencing ambiguity between GBA1 and its pseudogene GBAP1 affects transcriptomic analysis, revealing non-lysosomal functions in the brain and widespread annotation inaccuracies.

The paper identifies KAT8 and KANSL1 as regulators of PINK1-mitophagy linked to Parkinson's disease risk, suggesting a novel pathway for therapeutic targeting.

The paper shows that a significant portion of gene expression regulation in the human brain occurs post-transcriptionally in the cytoplasm, particularly for synaptic genes.

ggtranscript is an R package that visualizes and compares transcript isoforms using ggplot2, offering flexibility and ease of use for analyzing long-read sequencing data.

The paper identifies 1,513 unannotated 3'UTRs across 39 human tissues using a machine learning framework, highlighting their enrichment in brain and synaptic function.

recount3 provides uniformly processed RNA-seq data and tools for querying and analyzing large-scale human and mouse expression and splicing data.

The paper identifies human-lineage-specific genomic elements, called CNCRs, and shows their enrichment in neurological disease genes and APOE intron-3 retention transcripts in Alzheimer's disease.

This paper introduces dasper, an R/Bioconductor package that detects pathogenic splicing events from RNA-sequencing data with higher accuracy than existing methods.

Megadepth efficiently quantifies coverage in BigWig and BAM files, outperforming existing tools in speed and memory usage.

The paper examines mitochondrial-nuclear gene relationships in human brain tissue, finding cell-type specific variations and disruptions in Alzheimer’s disease.

The paper identifies and validates novel transcription regions across tissues, improving gene annotation for 63% of OMIM-morbid genes and highlights tissue-specific and functionally significant variants.

The paper identifies disease-relevant regulatory loci in human basal ganglia using genomic and transcriptomic data from 117 brains, highlighting splicing eQTLs and ASE analyses as sources of cell-specific regulatory information.

ERASE assesses enrichment of GWAS risk loci in ASE data and identifies splicing-related ASEs associated with Parkinson's disease.

This paper integrates eQTL and Parkinson’s disease GWAS data to identify 11 disease genes and pathways involved in PD risk through colocalisation, TWAS, and network analysis.

The paper identifies 5 new Alzheimer's risk loci by comparing mouse amyloid microglial response with human GWAS gene-based SNPs.

This study identifies a genetic variant at the TRIM11 locus associated with Progressive Supranuclear Palsy phenotype through GWAS and validates it in independent cohorts.

The paper develops a machine learning model to predict genes causing rare neurological disorders and shows it accurately identifies disease-associated genes.