Low-coverage whole genome sequencing for a highly selective cohort of severe COVID-19 patients
We generated a dataset consisting of 79 VCF files, and respective FASTQ and CRAM files, methodically generated using the GLIMPSE1 imputation algorithm leveraging the 1000 Genomes Project Phase 3 dataset as the reference panel of haplotypes. In total this dataset is composed of approximately 325 GB of FASTQ data, 156 GB of CRAM data, and 6 GB of VCF data. Our samples were specifically derived from sequenced DNA from a highly selective cohort of patients, mostly comprised of Iberian Populations in Spain (IBS) individuals but also containing some individuals with other genetic backgrounds, who presented severe COVID-19 symptoms during the initial wave of the SARS-CoV-2 pandemic in Madrid, Spain. On average, each VCF file in this rich dataset contains 9.49 million high-confidence single nucleotide variants [95%CI: 9.37 million - 9.61 million].
- 80 samples
- DAC: EGAC00001003435
- Technology: unspecified
COVID-19 Severity First Wave of Infection for Severe Patients in Madrid
We performed low-coverage whole genome sequencing of 80 samples (80 individuals) hospitalised due to COVID-19 during the first wave of infection in Madrid between March/June 2020. All patients had been confirmed by PCR and their phenotypes annotated using a purposely built controlled vocabulary. DUO:0000006 health/medical/biomedical research and clinical care DUO:0000018 not-for-profit use only DUO:0000020 collaboration required
Studies are experimental investigations of a particular phenomenon, e.g., case-control studies on a particular trait or cancer research projects reporting matching cancer normal genomes from patients.
| Study ID | Study Title | Study Type |
|---|---|---|
| Other |