pcr: an R package for quality assessment, analysis and testing of qPCR data
- Published
- Accepted
- Subject Areas
- Bioinformatics, Cell Biology, Computational Biology, Molecular Biology
- Keywords
- qPCR, R package, data analysis, Quality assessment
- Copyright
- © 2017 Ahmed et al.
- Licence
- This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Preprints) and either DOI or URL of the article must be cited.
- Cite this article
- 2017. pcr: an R package for quality assessment, analysis and testing of qPCR data. PeerJ Preprints 5:e3477v1 https://doi.org/10.7287/peerj.preprints.3477v1
Abstract
Background. Real-time quantitative PCR (qPCR) is a broadly used technique in the biomedical research. Currently, few different analysis models are used to determine the quality of data and to quantify the mRNA level across the experimental conditions. Methods. We developed an R package to implement methods for quality assessment, analysis and testing qPCR data for statistical significance. Double Delta CT and standard curve models were implemented to quantify the relative expression of target genes from CT in standard qPCR control-group experiments. In addition, calculation of amplification efficiency and curves from serial dilution qPCR experiments are used to assess the quality of the data. Finally, two-group testing and linear models were used to test for significance of the difference in expression control groups and conditions of interest.Results. Using two datasets from qPCR experiments, we applied different quality assessment, analysis and statistical testing in the pcr package and compared the results to the original published articles. The final relative expression values from the different models, as well as the intermediary outputs, were checked against the expected results in the original papers and were found to be accurate and reliable.Conclusion. The pcr package provides an intuitive and unified interface for its main functions to allow biologist to perform all necessary steps of qPCR analysis and produce graphs in a uniform way.
Author Comment
This is a submission to PeerJ for review.