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Real Time RT-PCR

Real Time RT-PCR

Real-time reverse transcription-polymerase chain reaction, or Real-time RT-PCR, is an analytical tool used to determine the expression level of target genes. The method involves converting mRNA to complementary DNA with the help of an enzyme known as reverse transcriptase, followed by the PCR amplification of the cDNA. These two processes can be performed simultaneously in a single tube or separately as a two-step reaction.
The real-time quantification of the number of amplified products is...

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Digital Polymerase Chain Reaction Assay for the Genetic Variation in a Sporadic Familial Adenomatous Polyposis Patient Using the Chip-in-a-tube Format

Digital Polymerase Chain Reaction Assay for the Genetic Variation in a Sporadic Familial Adenomatous Polyposis Patient Using the Chip-in-a-tube Format

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Digital PCR threshold robustness analysis and optimization using dipcensR.

Matthijs Vynck^1,2,3, Wim Trypsteen^1,3, Olivier Thas^1,4,5,6

¹Digital PCR Center (DIGPCR), Ghent University, Ghent, Belgium.

Briefings in Bioinformatics

|October 14, 2024

Summary

This summary is machine-generated.

Automated classification in digital PCR (dPCR) is crucial but error-prone. The new dipcensR software tool automates accuracy assessment for dPCR analysis, improving efficiency and reliability.

Keywords:

accuracy digital PCR multiplexing partition classification thresholding

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Area of Science:

Molecular Biology
Bioinformatics
Genomics

Background:

Digital polymerase chain reaction (dPCR) offers precise nucleic acid quantification.
High-throughput dPCR applications necessitate robust automated data analysis.
Current automated partition classification in dPCR requires manual accuracy evaluation, creating bottlenecks.

Purpose of the Study:

To develop an automated procedure for assessing the accuracy of dPCR partition classification.
To enhance the efficiency of high-throughput dPCR data analysis.
To provide a tool for optimizing dPCR partition classification robustness.

Main Methods:

Introduction of dipcensR, a novel data-analysis procedure for dPCR.
Implementation of a robustness evaluation for partition classification.
Development of an R package for dipcensR.

Main Results:

dipcensR automates the assessment of partition classification accuracy.
The tool flags classifications with low robustness, indicating a need for review.
dipcensR supports optional automatic optimization of partition classification for maximal robustness.

Conclusions:

dipcensR offers substantial efficiency gains for high-throughput dPCR applications.
Automated accuracy assessment and optimization improve the reliability of dPCR data.
The freely available R implementation facilitates widespread adoption of dipcensR.