The quantitative polymerase chain reaction (qPCR) is a versatile and popular assay for quantifying nucleic acids. With the recent expansion of the number of reactions per assay, there is a need for an accurate method to report the data suitable for automation. This book will describe such a method, based on machine learning analysis, and implement it with publicly available tools. This book is intended for researchers and will provide a detailed introduction to the programming language R, including references for the most common functions. This book will provide an advanced strategy for the objective analysis of qPCR data suitable for experts in the field and an introduction to qPCR and computational analysis for students.
Author(s): Luigi Marongiu
Series: Research Methodology and Data Analysis
Publisher: Nova Science Publishers
Year: 2022
Language: English
Pages: 148
Contents
Acknowledgments
Introduction
Chapter 1
The Role of qPCR in the Diagnosis of Diseases
Koch’s Postulates as Foundation of Diagnostics
Methods to Collect Genetic Material
Methods to Confirm the Presence of Microbial Genetic Material
Quantitative Polymerase Chain Reaction (qPCR) Assay
Listings
Chapter 2
Quantification by PCR
Primers Design
Elements of Quantification
Quality Control of the Fit-Point Method
The Issues of the Fit-Point Method
maxRatio
Listings
Chapter 3
Application of Machine Learning to maxRatio qPCR Analysis
Filtering maxRatio with the Expectation-Maximization Method
Filtering maxRatio with Support-Vector Machine
Real-life Example of the maxRatio/SVM Analytical Approach
Extending the SVM Classification
Listings
Conclusion
References
Author’s Contact Information
Index
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