Simulated SARS-CoV-2 Reads for Benchmarking Lineage Abundance Estimation

Eight independent datasets of simulated paired-end reads for evaluating the accuracy of SARS-CoV-2 lineage abundance estimates from amplicon-based and whole genome-based sequencing. The data includes 200 bp and 400 bp reads from the Netherlands and Texas, with varying amplicon counts and coverages, and each dataset contains 20 sets of reads generated with different random seeds. Jasper van Bemmelen from Delft University of Technology created this dataset, which is available via paperswithcode under an Open Access license.

Use Cases

• Benchmarking lineage abundance estimation algorithms based on simulated amplicon sequencing reads.
• Comparing the accuracy of amplicon-based versus whole genome-based sequencing methods for viral lineage detection.
• Evaluating the impact of read length (200 bp vs 400 bp) and coverage depth on lineage quantification performance.
• Testing the robustness of estimation tools using datasets generated with different random seeds.

Strengths

• Includes eight distinct datasets with controlled variables like read length, location, and sequencing method.
• Each independent dataset contains 20 replicate sets of reads generated with different random seeds for robustness testing.
• Provides specific GISAID accession IDs (EPI_SET_230825fe, EPI_SET_230825pe) for the source genomes used in simulations.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Last update date is unknown; freshness unverified.

Provenance

Source

paperswithcode

Collection Method

Simulated paired-end reads from amplicons determined by AmpliDiff and from full genomes.

Geography

Netherlands, Texas