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Digital PCR Partition Classification.
Vynck, Matthijs; Chen, Yao; Gleerup, David; Vandesompele, Jo; Trypsteen, Wim; Lievens, Antoon; Thas, Olivier; De Spiegelaere, Ward.
Afiliación
  • Vynck M; Digital PCR Consortium, Ghent University, Ghent, Belgium.
  • Chen Y; Department of Morphology, Imaging, Orthopedics, Rehabilitation and Nutrition, Faculty of Veterinary Medicine, Ghent University, Ghent, Belgium.
  • Gleerup D; Digital PCR Consortium, Ghent University, Ghent, Belgium.
  • Vandesompele J; Department of Morphology, Imaging, Orthopedics, Rehabilitation and Nutrition, Faculty of Veterinary Medicine, Ghent University, Ghent, Belgium.
  • Trypsteen W; Department of Applied Mathematics, Computer Science and Statistics, Faculty of Sciences, Ghent University, Ghent, Belgium.
  • Lievens A; Digital PCR Consortium, Ghent University, Ghent, Belgium.
  • Thas O; Department of Morphology, Imaging, Orthopedics, Rehabilitation and Nutrition, Faculty of Veterinary Medicine, Ghent University, Ghent, Belgium.
  • De Spiegelaere W; Digital PCR Consortium, Ghent University, Ghent, Belgium.
Clin Chem ; 69(9): 976-990, 2023 09 01.
Article en En | MEDLINE | ID: mdl-37401391
ABSTRACT

BACKGROUND:

Partition classification is a critical step in the digital PCR data analysis pipeline. A range of partition classification methods have been developed, many motivated by specific experimental setups. An overview of these partition classification methods is lacking and their comparative properties are often unclear, likely impacting the proper application of these methods. CONTENT This review provides a summary of all available digital PCR partition classification approaches and the challenges they aim to overcome, serving as a guide for the digital PCR practitioner wishing to apply them. We additionally discuss strengths and weaknesses of these methods, which can further guide practitioners in vigilant application of these existing methods. This review provides method developers with ideas for improving methods or designing new ones. The latter is further stimulated by our identification and discussion of application gaps in the literature, for which there are currently no or few methods available.

SUMMARY:

This review provides an overview of digital PCR partition classification methods, their properties, and potential applications. Ideas for further advances are presented and may bolster method development.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Reacción en Cadena de la Polimerasa Tipo de estudio: Qualitative_research Idioma: En Revista: Clin Chem Asunto de la revista: QUIMICA CLINICA Año: 2023 Tipo del documento: Article País de afiliación: Bélgica

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Reacción en Cadena de la Polimerasa Tipo de estudio: Qualitative_research Idioma: En Revista: Clin Chem Asunto de la revista: QUIMICA CLINICA Año: 2023 Tipo del documento: Article País de afiliación: Bélgica