Summary statistics of eQTLs obtained from single-nuclei RNA-seq in 8 major brain cell-types for mendelian randomisation

This dataset contains cis-eQTL summary statistics for 8 brain cell-types, generated on a snRNA-seq dataset on post-mortem brains from 391 individuals (full), as well as a controls-only (subset of full, 183 individuals).

Genotype dosage matrices were obtained with SeqArray, where 0 = homozygous alt, 1 = heterozygous, 2 = homozygous ref https://bioconductor.org/packages/release/bioc/manuals/SeqArray/man/SeqArray.pdf . The eQTL models as applied by MatrixEQTL therefore use "ref" as the effect allele (as implemented in their additive model).

The eQTL summary statistics for within the "full" and "controls-only" dataset have been packed into .tar.gz files for each cell-type, where unpacking will yield summary statistics by chromosome. Each file contains the following columns;

1. SNP (in rsid format)

2. gene (in symbol format)

3. t.stat (t-statistic as determined by MatrixEQTL)

4. p.value (linear model association p-value)

5. FDR (false discovery rate as determined by MatrixEQTL)

6. beta (effect size / slope of the linear model)

7. chrom (chromosome in "chrN" format)

8. position (SNP position, hg38 build)

9. effect_allele (this is the "ref" allele as described above)

10. other_allele (alternate allele)

11. maf (minor allele frequency, as determined by SeqArray on this dataset)

In addition, single-cell expression matrices in count format are available in the single-cell_data.tar archive for the full 391 individuals (2,348,438 cells). This archive contains processed single-cell counts as described in our manuscript for the 4 datasets included; "BRYOIS_192" (separated into "MS" and "AD" as per their publication), "MATTHEWS", "ROCHE_MPD92" and "MRC_60". In addition, a cell-level metadata file containing covariates and cell-type labels across all datasets is included (cell_level_metadata.rds). Cell barcodes and individual IDs have been renamed to preserve anonymity.

January 2025 update: Now published at Nature Genetics. https://www.nature.com/articles/s41588-024-02050-9