Methods for comparing multiple digital PCR experiments
Michał Burdukiewicz , Stefan Rödiger , Piotr Sobczyk , Mario Menschikowski , Peter Schierack , Paweł Mackiewicz
AbstractThe estimated mean copy per partition (λ) is the essential information from a digital PCR (dPCR) experiment because λ can be used to calculate the target concentration in a sample. However, little information is available how to statistically compare dPCR runs of multiple runs or reduplicates. The comparison of λ values from several runs is a multiple comparison problem, which can be solved using the binary structure of dPCR data. We propose and evaluate two novel methods based on Generalized Linear Models (GLM) and Multiple Ratio Tests (MRT) for comparison of digital PCR experiments. We enriched our MRT framework with computation of simultaneous confidence intervals suitable for comparing multiple dPCR runs. The evaluation of both statistical methods support that MRT is faster and more robust for dPCR experiments performed in large scale. Our theoretical results were confirmed by the analysis of dPCR measurements of dilution series. Both methods were implemented in the dpcR package (v. 0.2) for the open source R statistical computing environment.
|Journal series||Biomolecular Detection and Quantification, ISSN , e-ISSN 2214-7535|
|Publication size in sheets||0.5|
|Keywords in English||Digital PCR; GLM; Generalized Linear Models; Multiple comparison; dPCR|
|ASJC Classification||; ; ;|
|Score|| = 0.0, 04-09-2019, ArticleFromJournal|
= 5.0, 04-09-2019, ArticleFromJournal
|Publication indicators||: 2016 = 1.547|
* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or Perish system.