Evidence map›Paper›PMID 30659212›Full record

ArticleScientific reports2019

PrimerROC: accurate condition-independent dimer prediction using ROC analysis.

Andrew D Johnston, Jennifer Lu, Ke-Lin Ru, Darren Korbie, Matt Trau

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
1.7field-weighted citation impact, top 16% of its field
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

12 citing papers in PubMed, 39 citations in OpenAlex.

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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

5 authors at 1 institution in 1 country.

Andrew D JohnstonCentre for Personalized NanoMedicine, The University of Queensland, St Lucia, 4072, QLD, Australia.
Jennifer LuCentre for Personalized NanoMedicine, The University of Queensland, St Lucia, 4072, QLD, Australia.ORCID 0000-0002-1777-4788
Ke-Lin RuCentre for Personalized NanoMedicine, The University of Queensland, St Lucia, 4072, QLD, Australia.
Darren KorbieCentre for Personalized NanoMedicine, The University of Queensland, St Lucia, 4072, QLD, Australia. d.korbie@uq.edu.au.
Matt TrauCentre for Personalized NanoMedicine, The University of Queensland, St Lucia, 4072, QLD, Australia. m.trau@uq.edu.au.ORCID 0000-0001-5516-1280
The University of Queensland · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To-date systematic testing and comparison of the accuracy of available primer-dimer prediction software has never been conducted, due in part to a lack of tools able to measure the efficacy of Gibbs free energy (ΔG) calculations at predicting dimer formation in PCR. To address this we have developed a novel online tool called PrimerROC ( www.primer-dimer.com/roc/ ), which uses epidemiologically-based Receiver Operating Characteristic (ROC) curves to assess dimer prediction accuracy. Moreover, by integrating PrimerROC with our PrimerDimer prediction software we can determine a ΔG-based dimer-free threshold above which dimer formation is predicted unlikely to occur. Notably, PrimerROC determines this cut-off without any additional information such as salt concentration or annealing temperature, meaning that our PrimerROC method is an assay and condition independent prediction tool. To demonstrate the broad utility of PrimerROC we assessed the performance of seven publically available primer design and dimer analysis tools using a dataset of over 300 primer pairs. We found that our PrimerROC/PrimerDimer software consistently outperforms these other tools and can achieve predictive accuracies greater than 92%. To illustrate its predictive power this method was used in multiplex PCR design to successfully generate four resequencing assays containing up to 126 primers with no observable primer-primer amplification artefacts.

Identifiers

PMID30659212
PMCPMC6338771
OpenAlexW2909571268

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.