Quality Control
The DRAGEN TruSight Oncology 500 includes the following quality control analyses.
OpenRun QC The Run Metrics section of the metrics output report provides sequencing run quality metrics along with suggested values to determine if they are within an acceptable range. The overall percentage of reads passing filter is compared to a minimum threshold. For Read 1 and Read 2, the average percentage of bases ≥ Q30, which gives a prediction of the probability of an incorrect base call (Q‑score), are also compared to a minimum threshold. The following tables show run metric and quality threshold information for different systems.
The values in the Run Metrics section are listed as NA in the following situations:
If the analysis was started from FASTQ files.
If the analysis was started from BCL files and the InterOp files are missing or corrupt.
High Throughput Systems (NovaSeq 6000 or NovaSeq 6000Dx (RUO) Systems)
| Metric | Description | Recommended Guideline Quality Threshold | Variant Class |
|---|---|---|---|
PCT_PF_READS (%) | Total percentage of reads passing filter. | ≥55.0 | All |
PCT_Q30_R1 (%) | Percentage of Read 1 reads with quality score ≥ 30. | ≥80.0 | All |
PCT_Q30_R2 (%) | Percentage of Read 2 reads with quality score ≥ 30. | ≥80.0 | All |
Low Throughput Systems (NextSeq 500/550 Systems)
| Metric | Description | Recommended Guideline Quality Threshold | Variant Class |
|---|---|---|---|
PCT_PF_READS (%) | Total percentage of reads passing filter. | ≥80.0 | All |
PCT_Q30_R1 (%) | Percentage of Read 1 reads with quality score ≥ 30. | ≥80.0 | All |
PCT_Q30_R2 (%) | Percentage of Read 2 reads with quality score ≥ 30. | ≥80.0 | All |
DNA Sample QC
DRAGEN TruSight Oncology 500 uses QC metrics to assess the validity of analysis for DNA libraries that pass contamination quality control. If the library fails one or more quality metrics, then the corresponding variant type or biomarker is not reported, and the associated QC category in the report header displays FAIL. Additionally, a companion diagnostic result may not be available if it relies on QC passing for one or more of the following QC categories.
DNA library QC results are available in the MetricsOutput.tsv file. Refer to Metrics Output for details.
| Metric | Description | Recommended Guideline Quality Threshold | Variant Class |
|---|---|---|---|
CONTAMINATION_SCORE | The contamination score is based on VAF distribution of SNPs. | Contamination Score ≤ | All |
MEDIAN_EXON_COVERAGE | Median exon fragment coverage across all exon bases. | ≥ 150 | Small variant TMB |
PCT_EXON_50X | Percent exon bases with 50x fragment coverage. | ≥ 90.0 | Small variant TMB |
MEDIAN_INSERT_SIZE | The median fragment length in the sample. | ≥ 70 | Small variant TMB |
USABLE_MSI_SITES | The number of MSI sites usable for MSI calling. | ≥ 40 | MSI |
MEDIAN_BIN_COUNT_CNV_TARGET | The median raw bin count per CNV target. | ≥ 1.0 | CNV |
RNA Sample QC
The input for RNA Library QC is RNA alignment. Metrics and guideline thresholds can be found in the MetricsOutput.tsv file. Refer to Metrics Output for details.
| Metric | Description | Recommended Guideline Quality Threshold | Variant Class |
|---|---|---|---|
MEDIAN_CV_GENE_500X | The median CV for all genes with median coverage > 500x. Genes with median coverage > 500x are likely to be highly expressed. Higher CV median > 500x indicates an issue with library preparation (poor sample input and/or probes pulldown issue). | Fusion Splice | |
MEDIAN_INSERT_SIZE | The median fragment length in the sample. | ≥ 80 | Fusion Splice |
TOTAL_ON_TARGET_READS | The total number of reads that map to the target regions. | ≥ 9000000 | Fusion Splice |
GENE_MEDIAN_COVERAGE | The median deduped coverage across all genes in the RNA panel (55 genes). | N/A* | Fusion Splice |
To avoid failing RNA samples unnecessarily, Illumina does not recommend a universal threshold to determine RNA sample quality. RNA expression varies significantly across tissue types and a small panel size (55 genes), which makes normalization challenging. Tissue-specific thresholds could be considered for normalization.
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