DNAStack COVID19 SRA Data

Stream data with DDA:

from dagshub.streaming import DagsHubFilesystem

fs = DagsHubFilesystem(".", repo_url="https://dagshub.com/DagsHub-Datasets/dnastack-covid-19-sra-data-dataset")

fs.listdir("s3://dnastack-covid-19-sra-data")

Description:

The Sequence Read Archive (SRA) is the primary archive of high-throughput sequencing data, hosted by the National Institutes of Health (NIH). The SRA represents the largest publicly available repository of SARS-CoV-2 sequencing data. This dataset was created by DNAstack using SARS-CoV-2 sequencing data sourced from the SRA. Where possible, raw sequence data were processed by DNAstack through a unified bioinformatics pipeline to produce genome assemblies and variant calls. The use of a standardized workflow to produce this harmonized dataset allows public data generated using different methodologies to be combined and compared for a more powerful global analysis of available SARS-CoV-2 data, allowing researchers rapid access to aggregated downstream results for accelerated insight generation. Methodology: Reads from the SRA were extracted in FASTQ format, then entered into a different pipeline depending on the sequencing technology used to create the reads: the ARTIC protocol for Oxford Nanopore-derived reads; the SIGNAL pipeline for paired-end Illumina reads; and the CoSA pipeline (using DeepVariant for variant calling) for PacBio reads. Briefly, reads were primer-trimmed and aligned to the SARS-CoV-2 reference genome, following which contiguous regions were assembled and variant sites were called. Pangolin was then used to assign viral lineage based on the assembled genome.

Contact:

The Sequence Read Archive (SRA) is the primary archive of high-throughput sequencing data, hosted by the National Institutes of Health (NIH). The SRA represents the largest publicly available repository of SARS-CoV-2 sequencing data. This dataset was created by DNAstack using SARS-CoV-2 sequencing data sourced from the SRA. Where possible, raw sequence data were processed by DNAstack through a unified bioinformatics pipeline to produce genome assemblies and variant calls. The use of a standardized workflow to produce this harmonized dataset allows public data generated using different methodologies to be combined and compared for a more powerful global analysis of available SARS-CoV-2 data, allowing researchers rapid access to aggregated downstream results for accelerated insight generation. Methodology: Reads from the SRA were extracted in FASTQ format, then entered into a different pipeline depending on the sequencing technology used to create the reads: the ARTIC protocol for Oxford Nanopore-derived reads; the SIGNAL pipeline for paired-end Illumina reads; and the CoSA pipeline (using DeepVariant for variant calling) for PacBio reads. Briefly, reads were primer-trimmed and aligned to the SARS-CoV-2 reference genome, following which contiguous regions were assembled and variant sites were called. Pangolin was then used to assign viral lineage based on the assembled genome.

Update Frequency:

Rolling

Managed By:

https://dnastack.com/

Resources:

1. resource:
   • Description: SARS-CoV-2 raw sequencing and output data (FASTQ, BAM, FASTA, VCF)
   • ARN: arn:aws:s3:::dnastack-covid-19-sra-data
   • Region: us-west-2
   • Type: S3 Bucket
   • RequesterPays: False
   • Explore: Browse bucket

Tags:

aws-pds, bam, bioinformatics, coronavirus, COVID-19, fasta, fastq, global, genetic, genomic, health, life sciences, long read sequencing, SARS-CoV-2, vcf, virus, whole genome sequencing

Tutorials:

1. tutorial:
   • Title: Viral lineage assignment
   • URL: https://github.com/DNAstack/dnastack-open-data/tree/master/tutorials/assign_lineage
   • AuthorName: Heather Ward
   • Services: Batch, EC2, S3

Tools & Applications:

1. tools & applications:
   • Title: Viral AI
   • URL: https://viral.ai/collections/ncbi-sra
   • AuthorName: DNAstack