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Partitioning and subsampling statistics in compartment-based quantification methods

Loskyll, Manuel; Podbiel, Daniel; Guber, Andreas 1; Hoffmann, Jochen
1 Institut für Mikrostrukturtechnik (IMT), Karlsruher Institut für Technologie (KIT)

Abstract:

The precision of compartment-based quantification methods is subject to multiple effects, of which partitioning and subsampling play a major role. Partitioning is the process of aliquoting the sample liquid and consequently the contained target molecules, whereas subsampling denotes the fact that usually only a portion of a sample is analyzed. In this work, we present a detailed statistical description comprising the effects of partitioning and subsampling on the relative uncertainty of the test result. We show that the state-of-the-art binomial model does not provide accurate results for the level of subsampling present when analyzing the nucleic acid content of single specific cells. Hence, in this work we address partitioning and subsampling effects separately and subsequently combine them to derive the relative uncertainty of a test system and compare it for single cell content analysis and body fluid analysis. In point-of-care test systems the area for partitioning and detection is usually limited, which means that a trade-off between the number of partitions (related to a partitioning uncertainty) and the amount of analyzed volume (related to a subsampling uncertainty) might be inevitable. ... mehr


Verlagsausgabe §
DOI: 10.5445/IR/1000159116
Veröffentlicht am 04.07.2023
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Mikrostrukturtechnik (IMT)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2023
Sprache Englisch
Identifikator ISSN: 1932-6203
KITopen-ID: 1000159116
HGF-Programm 43.35.01 (POF IV, LK 01) Platform for Correlative, In Situ & Operando Charakterizat.
Erschienen in PLOS ONE
Verlag Public Library of Science (PLoS)
Band 18
Heft 5
Seiten Art.-Nr.: e0285784
Vorab online veröffentlicht am 15.05.2023
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