2021
DOI: 10.1101/2021.01.20.427420
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Multivariable Association Discovery in Population-scale Meta-omics Studies

Abstract: It is challenging to associate features such as human health outcomes, diet, environmental conditions, or other metadata to microbial community measurements, due in part to their quantitative properties. Microbiome multi-omics are typically noisy, sparse (zero-inflated), high-dimensional, extremely non-normal, and often in the form of count or compositional measurements. Here we introduce an optimized combination of novel and established methodology to assess multivariable association of microbial community fe… Show more

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Cited by 299 publications
(222 citation statements)
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References 66 publications
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“…To test associations involving bacteria taxa showing significant difference in abundance by HIV-1 status and clinical and immunological markers, correlation analysis was performed using R package Hmisc v4.5. Multivariate analysis of phenotypes with significant correlation was performed to ascertain association using Microbiome Multivariable Associations with Linear Models, MaAsLin2 (Mallick et al, 2021).…”
Section: Statistical Analysesmentioning
confidence: 99%
“…To test associations involving bacteria taxa showing significant difference in abundance by HIV-1 status and clinical and immunological markers, correlation analysis was performed using R package Hmisc v4.5. Multivariate analysis of phenotypes with significant correlation was performed to ascertain association using Microbiome Multivariable Associations with Linear Models, MaAsLin2 (Mallick et al, 2021).…”
Section: Statistical Analysesmentioning
confidence: 99%
“…distance-based redundancy analysis were performed using the R package vegan [28]. Per-feature tests for the association between specific microbial species and clinical biomarkers were done using the R package MaAsLin2 [29]. Further information regarding data processing and sample size calculation was previously reported [25].…”
Section: Discussionmentioning
confidence: 99%
“…Based on the ASV abundances from 16S rRNA sequencing, KEGG orthologs, EC numbers, and MetaCyc pathways were inferred. Within the MaAsLin2 framework, a linear regression with default settings was applied to test whether specific metabolic pathways were enriched by VD or MD [35].…”
Section: Picrustmentioning
confidence: 99%