Assessing and removing the effect of unwanted technical variations in microbiome data.
Journal
Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288
Informations de publication
Date de publication:
23 12 2022
23 12 2022
Historique:
received:
12
07
2022
accepted:
09
12
2022
entrez:
23
12
2022
pubmed:
24
12
2022
medline:
28
12
2022
Statut:
epublish
Résumé
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-thaw cycles, as likely major sources of unwanted variation in metagenomes. We also observed that these unwanted technical variations do not affect taxa uniformly, with freezing samples affecting taxa of class Bacteroidia the most, for example. Additionally, we benchmarked the performances of different correction methods, including ComBat, ComBat-seq, RUVg, RUVs, and RUV-III-NB. While RUV-III-NB performed consistently robust across our sensitivity and specificity metrics, most other methods did not remove unwanted variations optimally. Our analyses suggest that a careful consideration of possible technical confounders is critical during experimental design of microbiome studies, and that the inclusion of technical replicates is necessary to efficiently remove unwanted variations computationally.
Identifiants
pubmed: 36564466
doi: 10.1038/s41598-022-26141-x
pii: 10.1038/s41598-022-26141-x
pmc: PMC9789116
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
22236Informations de copyright
© 2022. The Author(s).
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