Beomjin Jang, Hong-Hee Won, Towfique Raj
This repository includes code and plots. Exploratory analysis and intermediate processing files are too large for this repository.
Preprint on MedRxiv is available.
SingleBrain eQTL browser is accessible at https://singlebrain.nygenome.org.
All cis-eQTL summary statistics are accessible at https://zenodo.org/records/14908182 and Bonferroni-corrected significant trans-eQTL summary statistics are accessible at https://zenodo.org/records/15860673.
All disease-/sex-specific eQTL summary statistics are accessible at https://zenodo.org/records/16051904.
A eQTL meta-analysis, called "SingleBrain", integrates publicly available snRNA-seq and genotype data from four independent cohorts: Fujita et al., Mathys et al., Gabitto et al., and Bryois et al.
a) Integration of publicly available single-nucleus RNA sequencing (snRNA-seq) and genotype data from four independent studies. A cis-eQTL meta-analysis was conducted across major central nervous system (CNS) cells and subtypes using a linear mixed model approach (multivariate multiple QTL, mmQTL). b) Cell proportion of each donor. c) Candidate genes and putative causal variants associated with neurodegenerative and neuropsychiatric diseases were identified through statistical colocalization, Mendelian randomization, and fine-mapping.
Code for processing data and plots.
To demonstrate how SAIGE-QTL [PMID: 38798318] identifies eQTLs and to compare the results with SingleBrain eQTLs, genome-wide test pipeline using SAIGE-QTL was established and cis-eQTL mapping was conducted using the dataset of Fujita et al..
SAIGE-QTL pipeline: https://github.com/RajLabMSSM/SAIGEQTL-pipeline.
All SAIGE-QTL summary statistics are accessible at https://zenodo.org/records/15860973.
Contributors names and contact info
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Beomjin Jang (beomjin.jang@mssm.edu)
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Hong-Hee Won (wonhh@skku.edu)
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Towfique Raj (towfique.raj@mssm.edu)