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Journal Articles Computational and Structural Biotechnology Journal Year : 2023

VTAM: A robust pipeline for validating metabarcoding data using controls


To obtain accurate estimates for biodiversity and ecological studies, metabarcoding studies should be carefully designed to minimize both false positive (FP) and false negative (FN) occurrences. Internal controls (mock samples and negative controls), replicates, and overlapping markers allow controlling metabarcoding errors but current metabarcoding software packages do not explicitly integrate these additional experimental data to optimize filtering. We have developed the metabarcoding analysis software VTAM, which uses explicitly these elements of the experimental design to find optimal parameter settings that minimize FP and FN occurrences. VTAM showed similar sensitivity, but a higher precision compared to two other pipelines using three datasets and two different markers (COI, 16S). The stringent filtering procedure implemented in VTAM aims to produce robust metabarcoding data to obtain accurate ecological estimates and represents an important step towards a non-arbitrary and standardized validation of metabarcoding data for conducting ecological studies.
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hal-03978642 , version 1 (08-02-2023)


Attribution - NonCommercial - NoDerivatives



Aitor González, Vincent Dubut, Emmanuel Corse, Reda Mekdad, Thomas Dechatre, et al.. VTAM: A robust pipeline for validating metabarcoding data using controls. Computational and Structural Biotechnology Journal, 2023, 21, pp.1151 - 1156. ⟨10.1016/j.csbj.2023.01.034⟩. ⟨hal-03978642⟩
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