Evidence map›Paper›PMID 16336641›Full record

ArticleBMC biotechnology2005

Standardisation of data from real-time quantitative PCR methods - evaluation of outliers and comparison of calibration curves.

Malcolm J Burns, Gavin J Nixon, Carole A Foy, Neil Harris

Abstract read
In one paragraph

Article in BMC biotechnology, 2005. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 76 papers.

0numbers the graph read from it
0cells of the map it votes in
76citing 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

76 citing papers in PubMed.

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  3. An Exploratory Analysis of Transcriptional Responses to Peanut Exposure inInternational journal of molecular sciences · 2026
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16 more citing papers are in PubMed but not listed here.

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.

Malcolm J BurnsBio-Molecular Innovation, LGC Limited, Queens Road, Teddington, Middlesex, TW11 0LY, UK. malcolm.burns@lgc.co.uk
Gavin J Nixon
Carole A Foy
Neil Harris

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAs real-time quantitative PCR (RT-QPCR) is increasingly being relied upon for the enforcement of legislation and regulations dependent upon the trace detection of DNA, focus has increased on the quality issues related to the technique. Recent work has focused on the identification of factors that contribute towards significant measurement uncertainty in the real-time quantitative PCR technique, through investigation of the experimental design and operating procedure. However, measurement uncertainty contributions made during the data analysis procedure have not been studied in detail. This paper presents two additional approaches for standardising data analysis through the novel application of statistical methods to RT-QPCR, in order to minimise potential uncertainty in results.

resultsExperimental data was generated in order to develop the two aspects of data handling and analysis that can contribute towards measurement uncertainty in results. This paper describes preliminary aspects in standardising data through the application of statistical techniques to the area of RT-QPCR. The first aspect concerns the statistical identification and subsequent handling of outlying values arising from RT-QPCR, and discusses the implementation of ISO guidelines in relation to acceptance or rejection of outlying values. The second aspect relates to the development of an objective statistical test for the comparison of calibration curves.

conclusionThe preliminary statistical tests for outlying values and comparisons between calibration curves can be applied using basic functions found in standard spreadsheet software. These two aspects emphasise that the comparability of results arising from RT-QPCR needs further refinement and development at the data-handling phase. The implementation of standardised approaches to data analysis should further help minimise variation due to subjective judgements. The aspects described in this paper will help contribute towards the development of a set of best practice guidelines regarding standardising handling and interpretation of data arising from RT-QPCR experiments.

Indexed as

BiotechnologyCalibrationClinical Laboratory TechniquesData Interpretation, StatisticalDNA PrimersEvaluation Studies as TopicGlyceraldehyde-3-Phosphate Dehydrogenase (Phosphorylating)HumansModels, StatisticalModels, TheoreticalReference StandardsRegression AnalysisReproducibility of ResultsResearch DesignReverse Transcriptase Polymerase Chain ReactionSensitivity and SpecificityDNA PrimersGlyceraldehyde-3-Phosphate Dehydrogenase (Phosphorylating)

Identifiers

PMID16336641
PMCPMC1326201

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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.