RNA-Seq Sample Data with Read Counts and Quality Metrics

Lewis D. Taylor published a dataset on figshare in May 2026. The table provides information on raw and clean read counts, base counts, sequencing error rates, quality scores (Q20 and Q30), and GC content for each sample. The dataset is small, with a file size of 11.6 KB.

Use Cases

• Calculate sequencing yield and efficiency based on raw and clean read counts.
• Assess data quality for downstream analysis based on Q20 and Q30 scores.
• Analyze nucleotide composition bias based on GC content per sample.
• Evaluate sequencing run performance based on error rates and base counts.

Strengths

• Dataset includes multiple quality metrics per sample, such as Q20, Q30, and GC content.
• File size is 11.6 KB, indicating a focused and manageable scope for initial inspection.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Description metadata is limited; actual data quality requires manual inspection after download.

Provenance

Source

figshare

Freshness

Last updated 2026-05-18 17:22:22; freshness should be verified.