To create a SummarySet object we first need GWAS summary data, like -the ones that can be obtained from IEU OpenGWAS through the -ieugwasr package. + To create a SummarySet object we first need GWAS summary data, like the ones that can be obtained from IEU OpenGWAS through the ieugw...
R script to update summary statistic files (Rapid_GWAS_low_confidence_filter_update.R)[https://github.com/Nealelab/UK_Biobank_GWAS/blob/master/Rapid_GWAS_low_confidence_filter_update.R] Requires data.table 1.12.2 R package Requires GWAS_list_low_confidence_filter_update.txt.gz file (or subse...
Causal associations between risk factors and common diseases inferred from GWAS summary data.###Common genetic variants in the FETUB locus, genetically predicted fetuin-B levels, and risk of insulin resistance in obese Chinese adults.###Association of Genetic Variants Related to Serum Calcium Levels...
Jian Yang and colleagues propose a method that integrates summary data from GWAS and eQTL studies to identify genes whose expression levels are associated with complex traits because of pleiotropy. They apply the method to five human complex traits and p
In this study, the SMR analysis is extended to an additional 28 complex traits and diseases (Table 1) which have summary data available in the public domain from large-scale GWAS. The results from the SMR analyses are made available in an online query database (http://www.cnsgenomics.com...
Complete GWAS summary datasets are now abundant. A large repository of curated, harmonised and QC'd datasets is available in theIEU GWAS database. They can be queried via theAPIdirectly, or through theieugwasrR package, or theieugwaspypython package. However, for faster querying that can be...
Fit SEM models to GWAS summary datawithout a SNP Run a GWAS where theSNP is includedin the structural equation model. Estimatefunctional enrichmentfor any parameter in a Genomic SEM model (e.g., factor variances). Run multivariate TWAS usingT-SEM ...
Various polygenic risk scores (PRS) methods have been proposed to combine the estimated effects of single nucleotide polymorphisms (SNPs) to predict genetic risks for common diseases, using data collected from genome-wide association studies (GWAS). Some
We propose a method (called SMR) that integrates summary-level data from GWAS with data from expression quantitative trait locus (eQTL) studies to identify genes whose expression levels are associated with a complex trait because of pleiotropy. We apply the method to five human complex traits ...
This package is part of theOpenGWAS project. It aims to reduce friction between connecting GWAS summary data sources to a range of analytical tools. See theStrategyvignette for more information. It aims to replace the originalgwasgluepackage but it is still in early development. ...