Please use this identifier to cite or link to this item:
http://hdl.handle.net/1942/40740
Title: | Digital PCR Partition Classification | Authors: | Vynck, Matthijs Chen, Yao Gleerup, David Vandesompele, Jo Trypsteen, Wim Lievens, Antoon THAS, Olivier De Spiegelaere, Ward |
Issue Date: | 2023 | Publisher: | OXFORD UNIV PRESS INC | Source: | CLINICAL CHEMISTRY, 69 (9) , p. 976-990 | 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. 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. | Notes: | De Spiegelaere, W (corresponding author), Salisburylaan 133,Entrance 78, B-9820 Merelbeke, Belgium. ward.despiegelaere@ugent.be |
Keywords: | Humans;Polymerase Chain Reaction | Document URI: | http://hdl.handle.net/1942/40740 | ISSN: | 0009-9147 | e-ISSN: | 1530-8561 | DOI: | 10.1093/clinchem/hvad063 | ISI #: | 001021889600001 | Rights: | American Association for Clinical Chemistry 2023. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com. Free access | Category: | A1 | Type: | Journal Contribution |
Appears in Collections: | Research publications |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Digital PCR Partition Classification.pdf | Published version | 9.51 MB | Adobe PDF | View/Open |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.