What quality control reveals about your surveillance results

Last updated: 5.3.2026

Time to read: 3 minutes

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‍The real-life impact of genomic surveillance

A recent study at UPMC Presbyterian Hospital showed what happens when genomic surveillance goes right: over two years, real-time WGS surveillance prevented 62 infections and nearly 5 deaths, with 95.6% of outbreaks stopped after intervention. Net savings exceeded $695,000, a 3.2-fold return on investment [1].

For genomic surveillance to deliver results like this, sequencing data quality has to be verified. Standard pipelines often fail to integrate quality control (QC) into the workflow, as it often takes too long to be efficient. This is why Solu integrates QC directly into a cloud-based platform delivering actionable results in minutes.

Your results are only as reliable as the data behind them

Passing QC doesn't mean the same thing for every analysis. Genomic surveillance pipelines like Solu look at species identification, AMR and virulence detection, plasmid typing, and SNP-based phylogenetics [2], each with different requirements for data quality.

This is why understanding where your data is strong and where it fails to meet requirements is critical for guiding efficient decisions in hospitals or microbiology labs.

Understanding what a quality control report actually means

Solu evaluates quality at two stages. Read-level metrics catch problems at the source: low base quality, insufficient coverage, contamination signals. Assembly-level metrics evaluate whether the reconstructed genome is complete and reliable enough for the analysis you need. If the assembly looks off, read-level metrics tell you why. Both layers are required to understand where problems arise and how to solve them.

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Solu makes the next step obvious

Solu doesn't stop at flagging the issue. Along with PASS/WARNING/FAIL labels, each scan comes with actionable recommendations to help you deal with the possible issues in your data. For example, a failed read quality check could mean a problem in your team's laboratory workflow. Solu connects the flag to the decision, so your team moves from upload to confident action in minutes.

With antibiotic resistance evolving faster than most hospitals can respond, the layer ensuring your data quality isn't optional.

Improve your genomic surveillance today with Solu.

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References

Sundermann AJ, Kumar P, Griffith MP, et al. Real-Time Genomic Surveillance for Enhanced Healthcare Outbreak Detection and Control: Clinical and Economic Impact. Clinical Infectious Diseases. 2025. DOI: 10.1093/cid/ciaf216
Solu. How Solu Analyzes Bacterial and Fungal Genomes. https://www.solugenomics.com/post/how-solu-analyzes-bacterial-and-fungal-genomes

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