i) Overview of the Project:
Despite a fairly broad implementation and application of real-time PCR, there still exists a vacuum in determining the correct procedures for the examination of quantitative real-time PCR; more explicitly, there is a need to determine appropriate procedures to attain the right kind of statistical treatment. In today’s various methods of data analysis, the key statistical inferences are not as exclusive as required like confidence interval. This paper presents and tends to relate four statistical models and approaches on the basis of standard curve method and methods for data analysis.
The first approach developed a multiple regression analysis model for the determination of ∆∆Ct directly from the approximation of interface of gene and treatment paraphernalia. The second approach used the analysis of covariance i.e. ANCOVA model where the derivation of ∆∆Ct could be made through the sequential evaluation and analysis of effects of concurrent variables. The remainder of the models chiefly involves the calculation of ∆Ct subsequently connected through the non-parametric comparable Wilcoxon test and a two group T-test. Moreover, a data quality control model was established, which was then applied through the SAS programs determined for all of the aforementioned approaches; analyzed data output was also presented for a sample set.
The SAS programs were used to put forward practical statistical solutions for real-time PCR data while the programs were also utilized to analyze a sample dataset. After a comprehensive analysis conducted through the approaches and models mentioned above, similar results were obtained.
ii) Guidance from research articles:
While conducting research and studying the retrospect, it was found that the real-time PCR data analysis i.e. the Polymerase Chain Reaction data analysis occupies a pivotal position in the biomedical sciences field. This method can very fairly be regarded as a revolution in the biomedical history. The real-time PCR is not different from the typical PCR, and is solely based on the fundamental principles of the Polymerase Chain Reaction (M. Tevfik Dorak, 2006). This method was primarily initiated roughly a decade ago, and has continued to gain popularity since its very inception.
The real-time PCR is different from the conventional PCR merely in a sense that it emphasizes on the entire process of the chain reaction in spite of the end product. Real-time PCR provides the biomedical scientists with a variety of analytical methods, detection chemistries and a constantly increasing number of platforms. Considering broadly, the real-time PCR is a part of molecular genetics, and is expanding throughout the globe.
The quantitative PCR i.e. qPCR entails a whole range of microbiological fronts comprising of environmental, clinical, food and industrial microbiology (Martin Fillon, 2012). This very visible impact of the qPCR has resulted in making it the center of all the primary attention and research. With a great deal of study, the qPCR technology has evolved a great deal. It has shape shifted from an expensive and complex to an affordable and sensitive technique. Also, with the latest developments and findings, this technique has become faster than ever before. qPCR has evolved into a benchmark for the detection of nucleic acids specifically in microbiology and broadly in biomedical research.
iii) Purpose of the project:
As an analysis tool, real-time PCR has proved to be one of the fastest and most dependable quantitative methods for the analysis and evaluation of gene expression. Its applications cover a vast paradigm and range broadly from microarray verification and pathogen quantification to drug therapy studies. As a procedure, the PCR has been segmented into three phases listed below;
- Exponential Phase
This is the primary segmentation of PCR whereby, a significant increase – exponentially – is observed in the product due to the reagents being non-limited. During this phase, the products ideally double in amount provided that the efficiency is a hundred percent.
- Linear Phase
In this phase, the product increases linearly due to a sudden limitation in the reagents.
- Plateau Phase