f67498a54f360b24b1e25b2787be0cd8c9067fc6 abenetpa Mon Dec 21 08:42:42 2020 -0800 corrected url link refs #26616 diff --git src/hg/makeDb/trackDb/human/covidHgiGwasR4Pval.html src/hg/makeDb/trackDb/human/covidHgiGwasR4Pval.html index 83bbb8a..6c8f8f4 100644 --- src/hg/makeDb/trackDb/human/covidHgiGwasR4Pval.html +++ src/hg/makeDb/trackDb/human/covidHgiGwasR4Pval.html @@ -1,128 +1,128 @@ <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>GWAS Data Release 4 (October 2020)</b></a> 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 of meta-analysis across multiple studies contributed by <a target="_blank" href="https://www.covid19hg.org/partners/">partners world-wide</a> to identify the genetic determinants of <b>SARS-CoV-2</b> infection susceptibility, disease severity and outcomes. 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 of COVID-19 host genetics research. 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><b>Severe COVID GWAS (A2):</b> Very severe respiratory confirmed covid vs. population (4336 cases from 12 studies)</li> <li><b>Hosp COVID GWAS (B2):</b> Hospitalized covid vs. population (7885 cases from 21 studies)</li> <li><b>Tested COVID GWAS (C1):</b> Covid vs. lab/self-reported negative (17965 cases from 33 studies)</li> <li><b>COVID GWAS (C2):</b> Covid vs. population (30937 cases from 36 studies)</li> </ul> Due to privacy concerns, these browser tracks exclude data provided by 23andMe contributed studies in the full analysis results. The actual study and case and control counts for the individual browser tracks are listed in the track labels. Details on -all studies can be found <a target="=blank" href="https://www.covid19hg.org/results/"><here></a>. +all studies can be found <a target="=blank" href="https://www.covid19hg.org/results/">here</a>. <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>p-value</b>). For better visualization of the data, only SNPs with p-values smaller than 1e-3 are displayed by default.</p> <p> The color saturation indicates effect size (beta coefficient): values over the median of effect size are brightly colored (bright red <span style='background-color: #ff0000;'> </span> , bright blue <span style='background-color: #0000ff;'> </span> ), those below the median are paler (light red <span style='background-color: #ffa0a0;'> </span> , light blue <span style='background-color: #a0a0ff;'> </span> ). </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>