0bce97ce16cc532f8a1792925e299ff2f2e1828c abenetpa Fri Sep 18 12:50:18 2020 -0700 added methods to desc page refs #26129 diff --git src/hg/makeDb/trackDb/human/covidHgiGwas.html src/hg/makeDb/trackDb/human/covidHgiGwas.html index 0cf3be2..3defc19 100644 --- src/hg/makeDb/trackDb/human/covidHgiGwas.html +++ src/hg/makeDb/trackDb/human/covidHgiGwas.html @@ -14,63 +14,84 @@ </p> <p> 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: </p> <ul> <li><b>ANA_C2_V2</b>: covid vs. population (6696 cases from 18 studies)</li> <li><b>ANA_B2_V2</b>: hospitalized covid vs. population (3199 cases from 8 studies)</li> </ul> <H2>Display Conventions</H2> <p> Displayed items are colored by <b>GWAS effect</b>: red for positive, blue for negative. -The height of the item reflects the <b>effect size</b> (beta coefficient). -The color saturation indicates <b>statistical significance</b>: p-values smaller than .05 +The height of the item reflects the <b>effect size</b>. 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 <b>statistical significance</b>: p-values smaller than 1e-5 are brightly colored (bright red <span style='background-color: #ff0000;'> </span> , bright blue <span style='background-color: #0000ff;'> </span> ), -those with less significance (p >= .05) are paler (light red +those with less significance (p >= 1e-5) are paler (light red <span style='background-color: #ffa0a0;'> </span> , light blue <span style='background-color: #a0a0ff;'> </span> -). 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 1e-3 are displayed by default. </p> <p> Each track has separate display controls and data can be filtered according to the <b>number of studies</b>, <b>minimum -log10 p-value</b>, and the <b>effect size (beta coefficient)</b>, using the track <b>Configure</b> options. </p> <p> <b>Mouseover</b> 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. </p> <H2>Methods</H2> <p> -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 +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 <a target=_blank href="https://www.covid19hg.org/results/">COVID-19 phenotype definitions</a>. +</p> +<p> +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 <b>SAIGE GWAS</b> 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 +<b>INFO > 0.6</b> and <b>MAF > 0.0001</b> 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. +</p> +<p> +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 <a target=_blank +href="https://github.com/covid19-hg/META_ANALYSIS">here</a>. More information about the prospective studies, processing pipeline, results and data sharing can be found <a target=_blank href="https://www.covid19hg.org/about/">here</a>. </p> <H2>Data Access</H2> <p> The data underlying these tracks and summary statistics results are publicly available in <a target=_blank href="https://www.covid19hg.org/results">COVID19-hg Release 3 (June 2020)</a>. The raw data can be explored interactively with the <a target="_blank" href="../cgi-bin/hgTables"> Table Browser</a>, or the <a target="_blank" href="../cgi-bin/hgIntegrator">Data Integrator</a>. Please refer to our <a href="https://groups.google.com/a/soe.ucsc.edu/forum/#!forum/genome" target="_blank">mailing list archives</a> for questions, or our <a target="_blank" href="../FAQ/FAQdownloads.html#download36">Data Access FAQ</a> for more information.