af1498d72e78e14d8b17ad2549f895611ead0cf2 dschmelt Fri Jan 8 16:17:41 2021 -0800 Code Review refs #26740 diff --git src/hg/makeDb/trackDb/human/covidHgiGwasR4.html src/hg/makeDb/trackDb/human/covidHgiGwasR4.html index f528b99..4e03962 100644 --- src/hg/makeDb/trackDb/human/covidHgiGwasR4.html +++ src/hg/makeDb/trackDb/human/covidHgiGwasR4.html @@ -1,131 +1,131 @@ <H2>Description</H2> <p> This track set shows the results of the <a target=_blank href="https://www.covid19hg.org/blog/2020-11-24-covid-19-hgi-results-for-data-freeze-4-october-2020/"<b>Data Release 4 (October 2020)</b></a> of <b>GWAS meta-analyses</b> from the <a target=_blank href="https://www.covid19hg.org/"> <b>COVID-19 Host Genetics Initiative (HGI)</b></a>: 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 <a target="_blank" href="https://www.covid19hg.org/partners/">partners world-wide</a> 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. At the time of this release, a total of 137 studies were registered with this effort. </p> <p> The specific phenotypes studied by the COVID-19 HGI are those that benefit from maximal sample size: primary analysis on disease severity. For the Data Release 4 the number of cases have increased by nearly ten-fold (over 30,000 COVID-19 cases and 1.47 million controls) by combining data from 34 studies across 16 countries. The increased sample size resulted in strong evidence of seven genomic regions associated with severe COVID-19, on chromosomes 3, 6, 9, 12, 19, and 21; and one additional signal on chromosome 3 associated with COVID-19 partial-susceptibility. The four tracks here are based on data from HGI meta-analyses A2, B2, C1, and C2, described here: </p> <ul> <li>Severe COVID GWAS (<b>A2</b>): Very severe respiratory confirmed covid vs. population (4933 cases from 14 studies)</li> <li>Hosp COVID GWAS (<b>B2</b>): Hospitalized covid vs. population (8638 cases from 23 studies)</li> <li>Tested COVID GWAS (<b>C1</b>): Covid vs. lab/self-reported negative (8638 cases from 23 studies)</li> <li>COVID GWAS (<b>C2</b>): Covid vs. population (30937 cases from 36 studies)</li> </ul> Due to privacy concerns, these browser tracks exclude some of the data in the full analysis results (specifically, data provided by 23andMe contributed studies). The actual study and case and control counts for the individual browser tracks are listed in the track labels (shown in the 'List subtracks' section above). <H2>Display Conventions</H2> <p> Displayed items are colored by <b>GWAS effect</b>: red for positive (harmful) effect, blue for negative (protective) effect. The height ('lollipop stem') of the item is based on statistical significance (<b>pvalue</b>) or effect size (<b>beta coefficient</b>). For better visualization of the data, only SNPs with p-values smaller than 1e-3 are displayed by default.</p> <p> For tracks based on effect size, the color saturation indicates statistical significance: 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 >= 1e-5) 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 track based on pvalue, the color brightness reflects the effect size.</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> COVID-19 Host Genetics Initiative (HGI) GWAS meta-analysis round 4 (October 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. </p> The meta-analysis was performed using fixed effects inverse variance weighting. 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 4 (October 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. </p> <H2>Credits</H2> <p> 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. </p> <H2>References</H2> <p> COVID-19 Host Genetics Initiative. <a href="https://www.ncbi.nlm.nih.gov/pubmed/32404885" target="_blank"> 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</a>. <em>Eur J Hum Genet</em>. 2020 Jun;28(6):715-718. PMID: <a href="https://www.ncbi.nlm.nih.gov/pubmed/32404885" target="_blank">32404885</a>; PMC: <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7220587/" target="_blank">PMC7220587</a> </p>