Metagenomic biomarker discovery and explanation

By Nicola Segata, Jacques Izard, Levi Waldron, Dirk Gevers, Larisa Miropolsky, W. Garrett, Curtis Huttenhower. Genome Biology, 2011

14,090 citations recorded by the source corpus.

This study describes and validates a new method for metagenomic biomarker discovery by way of class comparison, tests of biological consistency and effect size estimation. This addresses the challenge of finding organisms, genes, or pathways that consistently explain the differences between two or more microbial communities, which is a central problem to the study of metagenomics. We extensively validate our method on several microbiomes and a convenient online interface for the method is provided at http://huttenhower.sph.harvard.edu/lefse/.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/92c6dc9b4943d031200fc5646bc49e927b2cb750

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In Molecular Biology

Citations in the corpus

Applications of Machine Learning in Human Microbiome Studies: A Review on Feature Selection, Biomarker Identification, Disease Prediction and Treatment (2021, methodology): “Then, biological consistency is investigated using a set of pairwise tests among subclasses using the (unpaired) Wilcoxon rank-sum test, ﬁnally uses LDA to estimate the eﬀect size of each diﬀerentially abundant feature and perform dimension reduction (Segata et al., 2011).”
Comparison on the structure and function of the rhizosphere microbial community between healthy and root-rot Panax notoginseng (2016, methodology): “edu/galaxy/) to assess the effect size of each phylum (Segata et al., 2011).”
A Metagenomic Approach to Characterization of the Vaginal Microbiome Signature in Pregnancy (2012, methodology): “Linear discriminate analysis effect size (LEfSe) is a novel method developed to support for high dimensional class comparisons in metagenomics analysis [61].”
The Pancreatic Cancer Microbiome Promotes Oncogenesis by Induction of Innate and Adaptive Immune Suppression (2018, neutral): “LEfSe tool was used to identify differentially significant bacterial taxa between the cohorts with the Kruskal–Wallis test (51).”
Microbial biogeography of wine grapes is conditioned by cultivar, vintage, and climate (2013, methodology): “Significant taxonomic differences between sample conditions were also tested using LDA effect size (67).”
The microbiota modulates gut physiology and behavioral abnormalities associated with autism (2013, neutral): “, 2012), and (3) Galaxy platform-based LDA Effect Size analysis (LEfSe; Segata et al., 2011).”