Interactive metagenomic visualization in a Web browser

By Brian D. Ondov, Nicholas H. Bergman, Adam M. Phillippy. BMC Bioinformatics, 2011

1,980 citations recorded by the source corpus.

BackgroundA critical output of metagenomic studies is the estimation of abundances of taxonomical or functional groups. The inherent uncertainty in assignments to these groups makes it important to consider both their hierarchical contexts and their prediction confidence. The current tools for visualizing metagenomic data, however, omit or distort quantitative hierarchical relationships and lack the facility for displaying secondary variables.ResultsHere we present Krona, a new visualization tool that allows intuitive exploration of relative abundances and confidences within the complex hierarchies of metagenomic classifications. Krona combines a variant of radial, space-filling displays with parametric coloring and interactive polar-coordinate zooming. The HTML5 and JavaScript implementation enables fully interactive charts that can be explored with any modern Web browser, without the need for installed software or plug-ins. This Web-based architecture also allows each chart to be an independent document, making them easy to share via e-mail or post to a standard Web server. To illustrate Krona's utility, we describe its application to various metagenomic data sets and its compatibility with popular metagenomic analysis tools.ConclusionsKrona is both a powerful metagenomic visualization tool and a demonstration of the potential of HTML5 for highly accessible bioinformatic visualizations. Its rich and interactive displays facilitate more informed interpretations of metagenomic analyses, while its implementation as a browser-based application makes it extremely portable and easily adopted into existing analysis packages. Both the Krona rendering code and conversion tools are freely available under a BSD open-source license, and available from: http://krona.sourceforge.net.

Subfields: Molecular Biology, Spectroscopy

View Paper: https://www.semanticscholar.org/paper/8a77adf1bde82647db55126513053b5c4021e3e0

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Citations in the corpus

Identifying and visualizing functional PAM diversity across CRISPR-Cas systems (2016, methodology): “Krona plots are encapsulated in interactive HTML files, allowing interrogation of all sequences regardless of their enrichment score (Krona S1–S8).”
PLSDB: a resource of complete bacterial plasmids (2018, methodology): “The taxonomic composition of all collected plasmid records is provided by an interactive Krona plot (23) showing the count and percentage of records for different taxa and ranks in the complete dataset and for each used resource (INSDC and RefSeq).”
MOB-suite: software tools for clustering, reconstruction and typing of plasmids from draft assemblies (2018, neutral): “S1 using KRONA [23].”
PhyloSift: phylogenetic analysis of genomes and metagenomes (2014, methodology): “For easy visualization and exploratory data analysis, PhyloSift produces Krona plots [45] showing tax289 onomic probability mass in the 37 elite gene families, and a separate Krona plot showing taxonomic 290 probability mass distribution summed across the elite families and all other families.”
MetaWRAP—a flexible pipeline for genome-resolved metagenomic data analysis (2018, methodology): “…CONCOCT [19], MaxBin2 [20], metaBAT [21], CheckM [24], Binning_refiner [28], Kraken [29], Taxator-tk [30], BWA [32], SPAdes [34, 36], MegaHIT [35], KronaTools [37], Blobology [39], Mega-BLAST [45], TrimGalore [46], BMTagger [47], FastQC [48], Bowtie2 [49], Salmon [50, 51], and PROKKA [52].”
MGnify: the microbiome analysis resource in 2020 (2019, methodology): “The outputs of the amplicon pipeline, whether SSU-, LSU-or ITS-based, can be visualised on the website as Krona plots (34) (see Figure 1), bar charts and tables.”
Kraken: ultrafast metagenomic sequence classification using exact alignments (2014, methodology): “Krona [24] was used to generate all taxonomic distribution plots.”
Scalable metagenomic taxonomy classification using a reference genome database (2013, background): “Supplementary Figure shows the Taxonomic distribution of the synthetic viral and bacterial datasets as Krona plots [Ondov et al. (2011)] and Supplementary Figure shows the histogram of the percent identity of to the nearest genome match in the LMAT reference database.”
A comprehensive and comparative evaluation of primers for metabarcoding eDNA from fish (2020, methodology): “We used the Krona program (command ktImportTaxonomy) to visualise the taxonomic compositions of the sequences amplified by in silico PCR (Ondov et al., 2011).”
Metabarcoding reveals strong spatial structure and temporal turnover of zooplankton communities among marine and freshwater ports (2016, methodology): “Taxonomic abundance mosaic plots were generated with ggplot2 (Wickham, 2009) and hierarchical charts were created using Krona (Ondov et al., 2011).”
Metagenomics: Tools and Insights for Analyzing Next-Generation Sequencing Data Derived from Biodiversity Studies (2015, methodology): “It supports multiple visualization schemes including functional or taxonomic dendrograms, tag clouds, bar charts, and Krona taxonomic plots, 113 that allow hierarchical data to be explored in the form of a zoomable pie chart.”
High throughput ANI analysis of 90K prokaryotic genomes reveals clear species boundaries (2017, background): “International Journal of Systematic and Evolutionary Microbiology 66(2):1100–1103.”