Dataset Information

Statistical analysis of real-time PCR data.

ABSTRACT:

Background

Even though real-time PCR has been broadly applied in biomedical sciences, data processing procedures for the analysis of quantitative real-time PCR are still lacking; specifically in the realm of appropriate statistical treatment. Confidence interval and statistical significance considerations are not explicit in many of the current data analysis approaches. Based on the standard curve method and other useful data analysis methods, we present and compare four statistical approaches and models for the analysis of real-time PCR data.

Results

In the first approach, a multiple regression analysis model was developed to derive DeltaDeltaCt from estimation of interaction of gene and treatment effects. In the second approach, an ANCOVA (analysis of covariance) model was proposed, and the DeltaDeltaCt can be derived from analysis of effects of variables. The other two models involve calculation DeltaCt followed by a two group t-test and non-parametric analogous Wilcoxon test. SAS programs were developed for all four models and data output for analysis of a sample set are presented. In addition, a data quality control model was developed and implemented using SAS.

Conclusion

Practical statistical solutions with SAS programs were developed for real-time PCR data and a sample dataset was analyzed with the SAS programs. The analysis using the various models and programs yielded similar results. Data quality control and analysis procedures presented here provide statistical elements for the estimation of the relative expression of genes using real-time PCR.

SUBMITTER: Yuan JS

PROVIDER: S-EPMC1395339 | biostudies-literature | 2006 Feb

REPOSITORIES: biostudies-literature

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Publications

Statistical analysis of real-time PCR data.

Yuan Joshua S JS Reed Ann A Chen Feng F Stewart C Neal CN

BMC bioinformatics 20060222

<h4>Background</h4>Even though real-time PCR has been broadly applied in biomedical sciences, data processing procedures for the analysis of quantitative real-time PCR are still lacking; specifically in the realm of appropriate statistical treatment. Confidence interval and statistical significance considerations are not explicit in many of the current data analysis approaches. Based on the standard curve method and other useful data analysis methods, we present and compare four statistical appr ...[more]

PMID: 16504059

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Project description:BackgroundAs compared with traditional transgene copy number detection technologies such as Southern blot analysis, real-time PCR provides a fast, inexpensive and high-throughput alternative. However, the real-time PCR based transgene copy number estimation tends to be ambiguous and subjective stemming from the lack of proper statistical analysis and data quality control to render a reliable estimation of copy number with a prediction value. Despite the recent progresses in statistical analysis of real-time PCR, few publications have integrated these advancements in real-time PCR based transgene copy number determination.ResultsThree experimental designs and four data quality control integrated statistical models are presented. For the first method, external calibration curves are established for the transgene based on serially-diluted templates. The Ct number from a control transgenic event and putative transgenic event are compared to derive the transgene copy number or zygosity estimation. Simple linear regression and two group T-test procedures were combined to model the data from this design. For the second experimental design, standard curves were generated for both an internal reference gene and the transgene, and the copy number of transgene was compared with that of internal reference gene. Multiple regression models and ANOVA models can be employed to analyze the data and perform quality control for this approach. In the third experimental design, transgene copy number is compared with reference gene without a standard curve, but rather, is based directly on fluorescence data. Two different multiple regression models were proposed to analyze the data based on two different approaches of amplification efficiency integration. Our results highlight the importance of proper statistical treatment and quality control integration in real-time PCR-based transgene copy number determination.ConclusionThese statistical methods allow the real-time PCR-based transgene copy number estimation to be more reliable and precise with a proper statistical estimation. Proper confidence intervals are necessary for unambiguous prediction of trangene copy number. The four different statistical methods are compared for their advantages and disadvantages. Moreover, the statistical methods can also be applied for other real-time PCR-based quantification assays including transfection efficiency analysis and pathogen quantification.

Project description:Purpose: Transvaginal meshes for the treatment of Pelvic Organ Prolapse (POP) have been associated with severe adverse events and have been banned for clinical use in many countries. We recently reported the design of degradable poly (L-lactic acid)-co-poly (e-caprolactone) nanofibrous mesh (P nanomesh) bioengineered with endometrial mesenchymal stem/stromal cells (eMSC) for POP repair. We showed that such bioengineered meshes had high tissue integration as well as immunomodulatory effects in vivo. This study aimed to determine the key molecular players enabling eMSC- based foreign body response modulation. Methods: SUSD2+ eMSC were purified from single cell suspensions obtained from endometrial biopsies from cycling women by magnetic bead sorting. Electrospun P nanomeshes with and without eMSC were implanted in a NSG mouse skin wound repair model for 1 and 6 weeks. Quantitative PCR was used to assess the expression of extracellular matrix (ECM), cell adhesion, angiogenesis and inflammation genes as log2 fold changes compared to sham controls. Histology and immunostaining was used to visualize the ECM, blood vessels and multinucleated foreign body giant cells around implants. Results: Bioengineered P nanomesh/ eMSC constructs explanted after 6 weeks showed significant increase in 35 genes associated with ECM, ECM regulation, cell adhesion angiogenesis and immune response in comparison to P nanomesh alone. In the absence of eMSC, acute inflammatory genes were significantly elevated at 1 week. However, in presence of eMSC, there was an increased expression of anti-inflammatory genes including Mrc1 and Arg1 by 6 weeks. There was formation of multinucleated foreign body giant cells around both implants at 6 weeks that expressed CD206, a M2 macrophage marker. Conclusion: This study reveals that eMSC modulate the foreign body response to degradable P nanomeshes in vivo by altering the expression profile of mouse genes. eMSC reduce acute inflammatory and increase ECM synthesis, angiogenesis and anti-inflammatory gene expression at 6 weeks while forming newly synthesized collagen within the nanomeshes and neo-vasculature in close proximity. From a tissue engineering perspective, this is a hallmark of a highly successful implant, suggesting significant potential as alternative surgical constructs for the treatment of POP.

Dataset Information

Statistical analysis of real-time PCR data.

Background

Results

Conclusion

Publications

Statistical analysis of real-time PCR data.

Similar Datasets

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