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Published December 10, 2019 | Version v1
Dataset Open

GWAS summary statistics imputation support data and integration with PrediXcan MASHR

  • 1. The University of Chicago


Research group:


# GWAS summary statistics imputation, integration with PrediXcan MASHR-M


The file `sample_data.tar` contains all necessary files to perform imputation of GWAS summary statistics to the GTEx v8 QTL data set.

It includes 1000 Genomes individuals' genotypes as reference panel.

The `.tar` archive, upon uncompression, contains the following:



├── eur_ld.bed.gz
├── gtex_v8_eur_filtered_maf0.01_monoallelic_variants.txt.gz

├── coordinate_map
├── gwas
├── liftover
├── models
│   ├── eqtl
│   │   └── mashr
│   └── sqtl
│       └── mashr
└── reference_panel_1000G



`data/eur_ld.bed.gz` contains definitions of approximately independent LD-regions in hg38 (Berisa-Pickrell regions, lifted over)

`data/gtex_v8_eur_filtered_maf0.01_monoallelic_variants.txt.gz` is a snp annotation file, listing all GTEx v8 variants with MAF>0.01 in europeans.

`data/coordinate_map` contains precomputed mapping tables that MetaXcan tools can use to convert GWAS' genomic coordinates in GWAS between genome assemblies.

`data/gwas` contains a sample GWAS file for the purposes of a tutorial (data obtained from Nikpay et al (Nat Gen 2016)

`data/liftover` contains Liftover chains to map coordinates between human genome assemblies (used by full harmonization tools)

`data/models` contains PrediXcan MASHR-M models, and cross-tissue S-MultiXcan LD compilation, from eQTL and sQTL.

`data/reference_panel_1000G` contains 1000G hg38 genotypes, in parquet format, to be used by imputation tools.



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Additional details


  • Nikpay et al (Nat Gen 2016) "A comprehensive 1000 Genomes–based genome-wide association meta-analysis of coronary artery disease" doi 10.1038/ng.3396
  • Barbeira et al (Biorxiv 2019) "Widespread dose-dependent effects of RNA expression and splicing on complex diseases and traits" doi 10.1101/814350