EMPeror: a tool for visualizing high-throughput microbial community data

By Yoshiki Vazquez-Baeza, M. Pirrung, Antonio Gonzalez, Rob Knight. GigaScience, 2013

1,191 citations recorded by the source corpus.

BackgroundAs microbial ecologists take advantage of high-throughput sequencing technologies to describe microbial communities across ever-increasing numbers of samples, new analysis tools are required to relate the distribution of microbes among larger numbers of communities, and to use increasingly rich and standards-compliant metadata to understand the biological factors driving these relationships. In particular, the Earth Microbiome Project drives these needs by profiling the genomic content of tens of thousands of samples across multiple environment types.FindingsFeatures of EMPeror include: ability to visualize gradients and categorical data, visualize different principal coordinates axes, present the data in the form of parallel coordinates, show taxa as well as environmental samples, dynamically adjust the size and transparency of the spheres representing the communities on a per-category basis, dynamically scale the axes according to the fraction of variance each explains, show, hide or recolor points according to arbitrary metadata including that compliant with the MIxS family of standards developed by the Genomic Standards Consortium, display jackknifed-resampled data to assess statistical confidence in clustering, perform coordinate comparisons (useful for procrustes analysis plots), and greatly reduce loading times and overall memory footprint compared with existing approaches. Additionally, ease of sharing, given EMPeror’s small output file size, enables agile collaboration by allowing users to embed these visualizations via emails or web pages without the need for extra plugins.ConclusionsHere we present EMPeror, an open source and web browser enabled tool with a versatile command line interface that allows researchers to perform rapid exploratory investigations of 3D visualizations of microbial community data, such as the widely used principal coordinates plots. EMPeror includes a rich set of controllers to modify features as a function of the metadata. By being specifically tailored to the requirements of microbial ecologists, EMPeror thus increases the speed with which insight can be gained from large microbiome datasets.

Subfields: Ecology, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/85e6c84e6c971ae422926b0a6f168fa498d9ad1e

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Citations in the corpus

Exercise Alters Gut Microbiota Composition and Function in Lean and Obese Humans (2017, methodology): “A-diversity was calculated using QIIME version 1.9.0 (25) at an even sample depth of 14,038 sequences per sample, visualized using EMPeror (26), and analyzed by permutational multivariate analysis of variance (PERMANOVA).”
Targeting the Microbiota-Gut-Brain Axis: Prebiotics Have Anxiolytic and Antidepressant-like Effects and Reverse the Impact of Chronic Stress in Mice. (2017, neutral): “microbiota has principally been exploited to yield positive effects on brain health via probiotics with various bifidobacteria and lactobacilli strains shown to have anxiolytic and pro-cognitive effects in both rodents (7-10) and humans (11-14).”
American Gut: an Open Platform for Citizen Science Microbiome Research (2018, methodology): “We used Striped UniFrac as noted above to estimate beta-diversity (unweighted UniFrac) and EMPeror software (66) version 0.”
Gut Microbes and the Brain: Paradigm Shift in Neuroscience (2014, background): “Tools for tracking the dynamics of the microbiome are rapidly evolving (Caporaso et al., 2011; Vázquez-Baeza et al., 2013) and provide insights both into normal microbiome variation and into its changes in responses to therapy, including antibiotics (Lozupone et al., 2013) and fecal microbiota…”
Effects of library size variance, sparsity, and compositionality on the analysis of microbiome data (2015, methodology): “Also, we used python-based 362 QIIME version 1.9.0, with Emperor (Vazquez-Baeza et al. 2013).”
Human Gut Microbiota from Autism Spectrum Disorder Promote Behavioral Symptoms in Mice (2019, methodology): “PCoAs were visualized by EMPeror (Va´zquez-Baeza et al., 2013).”
Gut Microbiota Regulate Motor Deficits and Neuroinflammation in a Model of Parkinson's Disease (2016, positive): “Principle Coordinate Analysis (PCoA) projections were visualized using Emperor 0.9.4 (Vázquez-Baeza et al., 2013).”
Short‐chain fatty acids: microbial metabolites that alleviate stress‐induced brain–gut axis alterations (2018, neutral): “9.3-dev (Vazquez-Baeza et al. 2013).”