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:
Displayed items are colored by GWAS effect: red for positive, blue for negative. The height of the item reflects the effect size (beta coefficient). -The color saturation indicates statistical significance: P values smaller than .05 +The color saturation indicates statistical significance: p-values smaller than .05 are brightly colored (bright red , bright blue ), -those with less significance (P >= .05) are paler (light red +those with less significance (p >= .05) are paler (light red , light blue -). For better visualization of the data, only SNPs with P values smaller than .03 are +). For better visualization of the data, only SNPs with p-values smaller than .03 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 +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 +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.
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. More information about the prospective studies, processing pipeline, results and data sharing can be found here.