Assessing and removing the effect of unwanted technical variations in microbiome data.

ABSTRACT: Varying technologies and experimental approaches used in microbiome studies often lead to irreproducible results due to unwanted technical variations. Such variations, often unaccounted for and of unknown source, may interfere with true biological signals, resulting in misleading biological conclusions. In this work, we aim to characterize the major sources of technical variations in microbiome data and demonstrate how in-silico approaches can minimize their impact. We analyzed 184 pig faecal metagenomes encompassing 21 specific combinations of deliberately introduced factors of technical and biological variations. Using the novel Removing Unwanted Variations-III-Negative Binomial (RUV-III-NB), we identified several known experimental factors, specifically storage conditions and freeze-tha

SUBMITTER: Fachrul M 

PROVIDER: S-EPMC9789116 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature