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                <identifier>oai:data.mendeley.com/zb5p8tpkt3.1</identifier>
                <datestamp>2022-11-10T21:41:21Z</datestamp>
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    <dc:creator>cappuccio, antonio</dc:creator>
    <dc:title>Multi-objective optimization identifies a specific and interpretable COVID-19 host response signature</dc:title>
    <dc:publisher>Mendeley Data</dc:publisher>
    <dc:description>The identification of a COVID-19 host response signature in blood can increase understanding of SARS-CoV-2 pathogenesis and improve diagnostic tools. Applying a multi-objective optimization framework to both massive public and new multi-omics data, we identified a COVID-19 signature regulated at both transcriptional and epigenetic levels. We validated the signature’s robustness in multiple independent COVID-19 cohorts. Using public data from 8630 subjects and 53 conditions, we demonstrated no cross-reactivity with other viral and bacterial infections, COVID-19 comorbidities, and confounders. In contrast, all previously reported COVID-19 signatures were associated with significant cross-reactivity. The signature’s interpretation, based on cell-type deconvolution and single cell data analysis, revealed prominent yet complementary roles for plasmablasts and memory T cells. While the signal from plasmablasts mediated COVID-19 detection, the signal from memory T cells controlled against cross-reactivity with other viral infections. This framework identified a robust interpretable COVID-19 signature, and is broadly applicable in other disease contexts. </dc:description>
    <dc:subject>Host Response</dc:subject>
    <dc:subject>COVID-19 Diagnostics</dc:subject>
    <dc:type>Dataset</dc:type>
    <dc:identifier>doi:10.17632/zb5p8tpkt3.1</dc:identifier>
    <dc:identifier>oai:data.mendeley.com/zb5p8tpkt3.1</dc:identifier>
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    <dc:date>2022-11-10T21:41:21Z</dc:date>
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