COVID GWAS v3 Track Settings
 
GWAS meta-analyses from the COVID-19 Host Genetics Initiative   (All COVID-19 tracks)

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 COVID GWAS  COVID GWAS from the COVID-19 Host Genetics Initiative (6696 cases, 18 studies)   Schema 
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 Hosp COVID GWAS  Hospitalized COVID GWAS from the COVID-19 Host Genetics Initiative (3199 cases, 8 studies)   Schema 

Description

This track set shows GWAS meta-analyses from the COVID-19 Host Genetics Initiative (HGI): a collaborative effort to facilitate the generation, analysis and sharing of COVID-19 host genetics research. The COVID-19 HGI organizes meta-analyses across multiple studies contributed by partners world-wide to identify the genetic determinants of SARS-CoV-2 infection susceptibility and disease severity and outcomes. Moreover, the COVID-19 HGI also aims to provide a platform for study partners to share analytical results in the form of summary statistics and/or individual level data where possible.

The specific phenotypes studied by the COVID-19 HGI are those that benefit from maximal sample size: primary analysis on disease severity. Two meta-analyses are represented in this track:

  • ANA_C2_V2: covid vs. population (6696 cases from 18 studies)
  • ANA_B2_V2: hospitalized covid vs. population (3199 cases from 8 studies)

Display Conventions

Displayed items are colored by GWAS effect: red for positive, blue for negative. The height of the item reflects the effect size. The effect size, defined as the contribution of a SNP to the genetic variance of the trait, was measured as beta coefficient (beta). The higher the absolute value of the beta coefficient, the stronger the effect. The color saturation indicates statistical significance: p-values smaller than 1e-5 are brightly colored (bright red    , bright blue    ), those with less significance (p >= 1e-5) are paler (light red    , light blue    ). For better visualization of the data, only SNPs with p-values smaller than 1e-3 are displayed by default.

Each track has separate display controls and data can be filtered according to the number of studies, minimum -log10 p-value, and the effect size (beta coefficient), using the track Configure options.

Mouseover on items shows the rs ID (or chrom:pos if none assigned), both the non-effect and effect alleles, the effect size (beta coefficient), the p-value, and the number of studies. Additional information on each variant can be found on the details page by clicking on the item.

Methods

COVID-19 Host Genetics Initiative (HGI) GWAS meta-analysis round 3 (July 2020) results were used in this study. Each participating study partner submitted GWAS summary statistics for up to four of the COVID-19 phenotype definitions.

Data were generated from genome-wide SNP array and whole exome and genome sequencing, leveraging the impact of both common and rare variants. The statistical analysis performed takes into account differences between sex, ancestry, and date of sample collection. Alleles were harmonized across studies and reported allele frequencies are based on gnomAD version 3.0 reference data. Most study partners used the SAIGE GWAS pipeline in order to generate summary statistics used for the COVID-19 HGI meta-analysis. The summary statistics of individual studies were manually examined for inflation, deflation, and excessive number of false positives. Qualifying summary statistics were filtered for INFO > 0.6 and MAF > 0.0001 prior to meta-analyzing the entirety of the data. The meta-analysis was done using inverse variance weighting of effects method, accounting for strand differences and allele flips in the individual studies.

The meta-analysis results of variants appearing in at least three studies (analysis C2) or two studies (all other analyses) were made publicly available. The meta-analysis software and workflow are available here. More information about the prospective studies, processing pipeline, results and data sharing can be found here.

Data Access

The data underlying these tracks and summary statistics results are publicly available in COVID19-hg Release 3 (June 2020). The raw data can be explored interactively with the Table Browser, or the Data Integrator. Please refer to our mailing list archives for questions, or our Data Access FAQ for more information.

Credits

Thanks to the COVID-19 Host Genetics Initiative contributors and project leads for making these data available, and in particular to Rachel Liao, Juha Karjalainen, and Kumar Veerapen at the Broad Institute for their review and input during browser track development.

References

COVID-19 Host Genetics Initiative. The COVID-19 Host Genetics Initiative, a global initiative to elucidate the role of host genetic factors in susceptibility and severity of the SARS-CoV-2 virus pandemic. Eur J Hum Genet. 2020 Jun;28(6):715-718. PMID: 32404885; PMC: PMC7220587