flrpwr: Fluorescence Processing With R

The vast majority of qPCR practitioners rely on either manual interpretation of fluorescence curves or automated interpretation using manufacturers default software and settings associated with the thermal cyclers used to generate the data. This practice has three major vulnerabilities: 1. Manufacturers use proprietary algorithms that obscure transparency and impede validation. 2. Standardization across different labs and users is further limited when analysis software varies. 3. The analysis methods used are typically crude and do not incorporate advancements in methodology. To address these issues, we have developed a suite of functions in the R programming language and assembled them in the flrpwr package. The main functionality of the package is to... 1. read in raw fluorescence data from thermal cycler outputs 2. preprocess (normalization, slope correction, and standardization) 3. apply a baseline subtraction 4. analyze the properties of fluorescence curves 5. assign qualitative and quantitative measurements to the data 6. summarize and visualize the results The flrpwr package is able to flexibly and transparently apply multiple different methods of baseline subtraction and curve analysis simultaneously, allowing for standardization across different users, projects, and datasets in a programming language commonly used by scientists and resource managers. When using the most computationally intensive workflow in the flrpwr package users can expect to be able to process around 5 qPCR curves per second with the multimethi function. The package resides on the link shown in the Suggested Citation. Please consult this README along with other files (CONTRIBUTING.md, DISCLAIMER.md, LICENSE.md).