Evidence map›Paper›PMID 40128554›Full record

ArticleScientific reports2025

Preparation of robust synthetic control samples and their use in a metatranscriptomic clinical test.

Ryan Toma, Lan Hu, Guru Banavar, Momchilo Vuyisich

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Ryan TomaViome Research Institute, Viome Life Sciences, Inc., Seattle, WA, USA. ryan.toma@viome.com.
Lan HuViome Research Institute, Viome Life Sciences, Inc., Seattle, WA, USA.
Guru BanavarViome Research Institute, Viome Life Sciences, Inc., Seattle, WA, USA.
Momchilo VuyisichViome Research Institute, Viome Life Sciences, Inc., Seattle, WA, USA. momo@viome.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Metatranscriptomics (MT) has the potential to revolutionize the field of molecular diagnostics. Due to the complexity of MT diagnostic models, positive and negative control materials for specific disease indications can be difficult to obtain. Controls must often be sourced directly from patients. This introduces logistical burdens, assay variability, and limits high throughput clinical laboratory operations. To overcome this limitation, we developed a method for generating Synthetic Control (SC) samples, which duplicate the nucleic acid signature of complex clinical specimens and produce the desired test outcome. SCs can be easily and cost-effectively produced in large quantities (> 100,000 SCs per amplification cycle), enabling high throughput diagnostic testing. Here, we report the generation of Synthetic Positive Control (SPC) samples. SPCs were validated and implemented in a clinical laboratory. The SPCs produced robust positive signals (average OC risk score of 0.996) and high levels of reproducibility (%CV of 0.29%) in a high throughput automated CLIA laboratory. SCs are a novel and useful method for the generation of high quality controls for MT-based diagnostic tests, and their adoption could herald the widespread use of MT tests in molecular diagnostics.

Indexed as

Gene Expression ProfilingMolecular Diagnostic TechniquesTranscriptomeHumansReproducibility of Results

Identifiers

PMID40128554
PMCPMC11933260

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.