Statistical Modelling and Experimental Design for the Validation of Droplet Digital PCR Methods

Steffen Uhlig; Christopher Weidner; Bertrand Colson

doi:10.20944/preprints202204.0104.v1

Preprint Concept Paper Version 1 Preserved in Portico This version is not peer-reviewed

Version 1 : Received: 31 March 2022 / Approved: 12 April 2022 / Online: 12 April 2022 (08:46:49 CEST)

For the in-house validation of a droplet digital PCR method, a factorial experimental design was implemented. This design serves different purposes. On the one hand, it is an efficient design in relation to the workload involved in achieving a desirable level of reliability of variance estimates. On the other hand, it allows a partitioning of total variance into different components, thus providing information regarding the dominant sources of random variation. The statistical modelling reflects the actual measurement mechanism, establishing relationships between nominal target DNA copies per well, the range of variation of copy numbers per droplet, probability of detection values, and estimated numbers of copies.

Method validation; droplet digital PCR; orthogonal factorial design; variance components; Poisson assumption; cloglog model; target DNA copies per droplet; Monte Carlo; prediction interval

Computer Science and Mathematics, Mathematical and Computational Biology

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Statistical Modelling and Experimental Design for the Validation of Droplet Digital PCR Methods

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