eRNA GReX
Description
This dataset contains all model weights and corresponding datasets generated by Betti et al. in the manuscript Genetically regulated enhancer RNA expression predicts enhancer-promoter contact frequency and reveals genetic mechanisms at complex trait-associated loci. The following are the contents of the sub-directories in this dataset:
- coloc: Colocalization results for genome-wide significant (p < 5 x 10-8) GWAS associations in the UK Biobank with eRNA and canonical gene eQTLs (Supplementary Tables 11 and 12).
- contact_model_training: Input datasets from whole blood and brain, respectively, that were used to train the neural network-based models of contact frequency.
- eqtl_mapping: eQTLs mapped across 49 cell and tissue types for both eRNAs and canonical genes.
- scz_mr: Inputs and results for Mendelian randomization analysis of eRNA and canonical gene-based TWAS of schizophrenia.
- scz_twas: eRNA and canonical gene-based TWAS results of schizophrenia.
- trained_models: Model weights and SNP covariance matrices for genetically regulated eRNA expression (GReX) across 49 cell and tissue types.
- uk_biobank_twas: eRNA-based TWAS summary statistics for 4,671 UK Biobank traits across 49 cell and tissue types.
Please cite:
Betti, M.J., Aldrich, M.C., Lin, P., & Gamazon, E.R. (2024). Genetically regulated enhancer RNA expression predicts enhancer-promoter contact frequency and reveals genetic mechanisms at complex trait-associated loci. Preprint.
Betti, M.J., Aldrich, M.C., Lin, P., & Gamazon, E.R. (2024). eRNA GReX (Version 1.0). Zenodo. 10.5281/zenodo.11212496
Files
erna-grex.zip
Files
(25.3 GB)
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Additional details
Software
- Repository URL
- https://github.com/mjbetti/erna-grex
- Programming language
- Jupyter Notebook , R
- Development Status
- Active