End-to-End Data Automation for Pooled Sample SARS-CoV-2 Using R and Other Open-Source Tools. (4th January 2023)

• Record Type: Journal Article
• Authors: Mobini, Mahdi; Matic, Nancy; Gugten, J Grace Van Der; Ritchie, Gordon; Lowe, Christopher F; Holmes, Daniel T
• Is Part Of: Journal of applied laboratory medicine. Volume 8:Number 1(2023)
• Page Start: 41
• Page End: 52
• Publication Date: 2023-01-04
• Subjects: automation -- liquid handling -- pooling -- COVID -- R programming language; Clinical chemistry -- Periodicals; Diagnosis, Laboratory -- Periodicals; 616.0756
• DOI: 10.1093/jalm/jfac109
• Languages: English
• ISSNs: 2576-9456

Abstract

Abstract: Background: Due to supply chain shortages of reagents for real-time (RT)-PCR for SARS-CoV-2 and increasing demand on technical staff, an end-to-end data automation strategy for SARS-CoV-2 sample pooling and singleton analysis became necessary in the summer of 2020. Methods: Using entirely open source software tools—Linux, bash, R, RShiny, ShinyProxy, and Docker—we developed a modular software application stack to manage the preanalytical, analytical, and postanalytical processes for singleton and pooled testing in a 5-week time frame. Results: Pooling was operationalized for 81 days, during which time 64 pooled runs were performed for a total of 5320 sample pools and approximately 21 280 patient samples in 4:1 format. A total of 17 580 negative pooled results were released in bulk. After pooling was discontinued, the application stack was used for singleton analysis and modified to release all viral RT-PCR results from our laboratory. To date, 236 109 samples have been processed avoiding over 610 000 transcriptions. Conclusions: We present an end-to-end data automation strategy connecting 11 devices, one network attached storage, 2 Linux servers, and the laboratory information system.