Compact graphical representation of phylogenetic data and metadata with GraPhlAn

By F. Asnicar, George Weingart, Timothy L. Tickle, Curtis Huttenhower, Nicola Segata. PeerJ, 2015

721 citations recorded by the source corpus.

The increased availability of genomic and metagenomic data poses challenges at multiple analysis levels, including visualization of very large-scale microbial and microbial community data paired with rich metadata. We developed GraPhlAn (Graphical Phylogenetic Analysis), a computational tool that produces high-quality, compact visualizations of microbial genomes and metagenomes. This includes phylogenies spanning up to thousands of taxa, annotated with metadata ranging from microbial community abundances to microbial physiology or host and environmental phenotypes. GraPhlAn has been developed as an open-source command-driven tool in order to be easily integrated into complex, publication-quality bioinformatics pipelines. It can be executed either locally or through an online Galaxy web application. We present several examples including taxonomic and phylogenetic visualization of microbial communities, metabolic functions, and biomarker discovery that illustrate GraPhlAn’s potential for modern microbial and community genomics.

Subfields: Ecology, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/647e117ecef295b10c965f9d60c986e02536e3c1

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Ecology

In Molecular Biology

Citations in the corpus

BugBase predicts organism-level microbiome phenotypes (2017, neutral): “9 [39].”
High-Specificity Targeted Functional Profiling in Microbial Communities with ShortBRED (2015, positive): “This figure was produced using GraPhlAn [27].”
Microbial strain-level population structure and genetic diversity from metagenomes (2017, background): “This parallels the assessment of within-subject strain retention that has been carried out previously for targeted pathogen isolates (Covacci et al. 1999; Nowrouzian et al. 2005; Bidmos et al. 2011).”
Soil pH is the primary factor driving the distribution and function of microorganisms in farmland soils in northeastern China (2019, methodology): “Using the GraPhlAn visual tool (Asnicar et al. 2015), a hierarchical tree was constructed for the composition of all samples at each classification level.”
ETE 3: Reconstruction, Analysis, and Visualization of Phylogenomic Data (2016, methodology): “Although several software packages are available for the standalone exploration of trees (Letunic and Bork 2007; Huson and Scornavacca 2012; Asnicar et al. 2015) and the programmatic manipulation of data (Paradis et al. 2004; Knight et al. 2007; Sukumaran and Holder 2010; Vos et al. 2011; Talevich…”