Benchmarking Differential Abundance Analysis Methods for Correlated Microbiome Sequencing Data

Overview

Journal Brief Bioinform

Publisher Oxford University Press

Specialty Biology

Date 2023 Jan 8

PMID 36617187

Authors

Lu Yang

Jun Chen

Affiliations

Soon will be listed here.

Abstract

Differential abundance analysis (DAA) is one central statistical task in microbiome data analysis. A robust and powerful DAA tool can help identify highly confident microbial candidates for further biological validation. Current microbiome studies frequently generate correlated samples from different microbiome sampling schemes such as spatial and temporal sampling. In the past decade, a number of DAA tools for correlated microbiome data (DAA-c) have been proposed. Disturbingly, different DAA-c tools could sometimes produce quite discordant results. To recommend the best practice to the field, we performed the first comprehensive evaluation of existing DAA-c tools using real data-based simulations. Overall, the linear model-based methods LinDA, MaAsLin2 and LDM are more robust than methods based on generalized linear models. The LinDA method is the only method that maintains reasonable performance in the presence of strong compositional effects.

Citing Articles

ZINQ-L: a zero-inflated quantile approach for differential abundance analysis of longitudinal microbiome data.

Li S, Li R, Lee J, Zhao N, Ling W Front Genet. 2025; 15:1494401.

PMID: 39944355 PMC: 11814158. DOI: 10.3389/fgene.2024.1494401.

A realistic benchmark for differential abundance testing and confounder adjustment in human microbiome studies.

Wirbel J, Essex M, Forslund S, Zeller G Genome Biol. 2024; 25(1):247.

PMID: 39322959 PMC: 11423519. DOI: 10.1186/s13059-024-03390-9.

The Beneficial Effects of subsp. DSM 27449 in a Letrozole-Induced Polycystic Ovary Syndrome Rat Model.

Lee Y, Cheng S, Lin Y, Wu C, Tsai Y Int J Mol Sci. 2024; 25(16).

PMID: 39201391 PMC: 11354393. DOI: 10.3390/ijms25168706.

Next-generation data filtering in the genomics era.

Hemstrom W, Grummer J, Luikart G, Christie M Nat Rev Genet. 2024; 25(11):750-767.

PMID: 38877133 DOI: 10.1038/s41576-024-00738-6.

Environmental bacteria increase population growth of hydra at low temperature.

Miklos M, Cseri K, Laczko L, Kardos G, Fraune S, Tokolyi J Front Microbiol. 2023; 14:1294771.

PMID: 38088971 PMC: 10715282. DOI: 10.3389/fmicb.2023.1294771.

References

Kuczynski J, Lauber C, Walters W, Parfrey L, Clemente J, Gevers D . Experimental and analytical tools for studying the human microbiome. Nat Rev Genet. 2011; 13(1):47-58. PMC: 5119550. DOI: 10.1038/nrg3129. View

. Household paired design reduces variance and increases power in multi-city gut microbiome study in multiple sclerosis. Mult Scler. 2020; :1352458520924594. PMC: 7968892. DOI: 10.1177/1352458520924594. View

Duncan K, Carey-Ewend K, Vaishnava S . Spatial analysis of gut microbiome reveals a distinct ecological niche associated with the mucus layer. Gut Microbes. 2021; 13(1):1874815. PMC: 8253138. DOI: 10.1080/19490976.2021.1874815. View

Edwinson A, Yang L, Peters S, Hanning N, Jeraldo P, Jagtap P . Gut microbial β-glucuronidases regulate host luminal proteases and are depleted in irritable bowel syndrome. Nat Microbiol. 2022; 7(5):680-694. PMC: 9081267. DOI: 10.1038/s41564-022-01103-1. View

Robinson M, Oshlack A . A scaling normalization method for differential expression analysis of RNA-seq data. Genome Biol. 2010; 11(3):R25. PMC: 2864565. DOI: 10.1186/gb-2010-11-3-r25. View

Zhou H, He K, Chen J, Zhang X . LinDA: linear models for differential abundance analysis of microbiome compositional data. Genome Biol. 2022; 23(1):95. PMC: 9012043. DOI: 10.1186/s13059-022-02655-5. View

Chen J, Bushman F, Lewis J, Wu G, Li H . Structure-constrained sparse canonical correlation analysis with an application to microbiome data analysis. Biostatistics. 2012; 14(2):244-58. PMC: 3590923. DOI: 10.1093/biostatistics/kxs038. View

Nishiwaki H, Hamaguchi T, Ito M, Ishida T, Maeda T, Kashihara K . Short-Chain Fatty Acid-Producing Gut Microbiota Is Decreased in Parkinson's Disease but Not in Rapid-Eye-Movement Sleep Behavior Disorder. mSystems. 2020; 5(6). PMC: 7771407. DOI: 10.1128/mSystems.00797-20. View

Bokulich N, Dillon M, Zhang Y, Rideout J, Bolyen E, Li H . q2-longitudinal: Longitudinal and Paired-Sample Analyses of Microbiome Data. mSystems. 2018; 3(6). PMC: 6247016. DOI: 10.1128/mSystems.00219-18. View

10.

Charlson E, Chen J, Custers-Allen R, Bittinger K, Li H, Sinha R . Disordered microbial communities in the upper respiratory tract of cigarette smokers. PLoS One. 2010; 5(12):e15216. PMC: 3004851. DOI: 10.1371/journal.pone.0015216. View

11.

Dennis B, Ponciano J, Taper M . Replicated sampling increases efficiency in monitoring biological populations. Ecology. 2010; 91(2):610-20. DOI: 10.1890/08-1095.1. View

12.

Hu Y, Satten G . Testing hypotheses about the microbiome using the linear decomposition model (LDM). Bioinformatics. 2020; 36(14):4106-4115. PMC: 8453243. DOI: 10.1093/bioinformatics/btaa260. View

13.

Warton D, Hui F . The arcsine is asinine: the analysis of proportions in ecology. Ecology. 2011; 92(1):3-10. DOI: 10.1890/10-0340.1. View

14.

Chen L, Reeve J, Zhang L, Huang S, Wang X, Chen J . GMPR: A robust normalization method for zero-inflated count data with application to microbiome sequencing data. PeerJ. 2018; 6:e4600. PMC: 5885979. DOI: 10.7717/peerj.4600. View

15.

Morgan X, Kabakchiev B, Waldron L, Tyler A, Tickle T, Milgrom R . Associations between host gene expression, the mucosal microbiome, and clinical outcome in the pelvic pouch of patients with inflammatory bowel disease. Genome Biol. 2015; 16:67. PMC: 4414286. DOI: 10.1186/s13059-015-0637-x. View

16.

. The Integrative Human Microbiome Project. Nature. 2019; 569(7758):641-648. PMC: 6784865. DOI: 10.1038/s41586-019-1238-8. View

17.

Faust K, Raes J . Microbial interactions: from networks to models. Nat Rev Microbiol. 2012; 10(8):538-50. DOI: 10.1038/nrmicro2832. View

18.

Silverman J, Roche K, Mukherjee S, David L . Naught all zeros in sequence count data are the same. Comput Struct Biotechnol J. 2020; 18:2789-2798. PMC: 7568192. DOI: 10.1016/j.csbj.2020.09.014. View

19.

Morton J, Marotz C, Washburne A, Silverman J, Zaramela L, Edlund A . Establishing microbial composition measurement standards with reference frames. Nat Commun. 2019; 10(1):2719. PMC: 6586903. DOI: 10.1038/s41467-019-10656-5. View

20.

Weiss S, Xu Z, Peddada S, Amir A, Bittinger K, Gonzalez A . Normalization and microbial differential abundance strategies depend upon data characteristics. Microbiome. 2017; 5(1):27. PMC: 5335496. DOI: 10.1186/s40168-017-0237-y. View