Dataset Information

FCI: an R-based algorithm for evaluating uncertainty of absolute real-time PCR quantification.

ABSTRACT:

Background

FCI is an R code for analyzing data from real-time PCR experiments. This algorithm estimates standard curve features as well as nucleic acid concentrations and confidence intervals according to Fieller's theorem.

Results

In order to describe the features of FCI four situations were selected from real data collected during an international external quality assessment program for quantitative assays based on real-time PCR. The code generates a diagnostic figure suitable for assessing the quality of the quantification process.

Conclusion

We have provided a freeware programme using this algorithm specifically designed to increase the information content of the real-time PCR assay.

SUBMITTER: Verderio P

PROVIDER: S-EPMC2245902 | biostudies-literature | 2008 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

FCI: an R-based algorithm for evaluating uncertainty of absolute real-time PCR quantification.

Verderio Paolo P Pizzamiglio Sara S Gallo Fabio F Ramsden Simon C SC

BMC bioinformatics 20080110

<h4>Background</h4>FCI is an R code for analyzing data from real-time PCR experiments. This algorithm estimates standard curve features as well as nucleic acid concentrations and confidence intervals according to Fieller's theorem.<h4>Results</h4>In order to describe the features of FCI four situations were selected from real data collected during an international external quality assessment program for quantitative assays based on real-time PCR. The code generates a diagnostic figure suitable f ...[more]

PMID: 18186926

Similar Datasets

Project description:BackgroundIn real-time PCR data analysis, the cycle threshold (CT) method is currently the gold standard. This method is based on an assumption of equal PCR efficiency in all reactions, and precision may suffer if this condition is not met. Nonlinear regression analysis (NLR) or curve fitting has therefore been suggested as an alternative to the cycle threshold method for absolute quantitation. The advantages of NLR are that the individual sample efficiency is simulated by the model and that absolute quantitation is possible without a standard curve, releasing reaction wells for unknown samples. However, the calculation method has not been evaluated systematically and has not previously been applied to a TaqMan platform.AimTo develop and evaluate an automated NLR algorithm capable of generating batch production regression analysis.ResultsTotal RNA samples extracted from human gastric mucosa were reverse transcribed and analysed for TNFA, IL18 and ACTB by TaqMan real-time PCR. Fluorescence data were analysed by the regular CT method with a standard curve, and by NLR with a positive control for conversion of fluorescence intensity to copy number, and for this purpose an automated algorithm was written in SPSS syntax. Eleven separate regression models were tested, and the output data was subjected to Altman-Bland analysis. The Altman-Bland analysis showed that the best regression model yielded quantitative data with an intra-assay variation of 58% vs. 24% for the CT derived copy numbers, and with a mean inter-method deviation of x 0.8.ConclusionNLR can be automated for batch production analysis, but the CT method is more precise for absolute quantitation in the present setting. The observed inter-method deviation is an indication that assessment of the fluorescence conversion factor used in the regression method can be improved. However, the versatility depends on the level of precision required, and in some settings the increased cost effectiveness of NLR may justify the lower precision.

Dataset Information

FCI: an R-based algorithm for evaluating uncertainty of absolute real-time PCR quantification.

Background

Results

Conclusion

Publications

FCI: an R-based algorithm for evaluating uncertainty of absolute real-time PCR quantification.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets