ArticleBioinformatics advances2022
Evidente-a visual analytics tool for data enrichment in SNP-based phylogenetic trees.
Article in Bioinformatics advances, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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0 citing papers in PubMed, 5 citations in OpenAlex.
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Motivation: A common practice in the analysis of pathogens and their strains is using single-nucleotide polymorphisms (SNPs) to reconstruct their evolutionary history. However, genome-wide SNP-based phylogenetic trees are rarely analyzed without any further information. Including the underlying SNP data together with further metadata on the respective samples in the exploration process can facilitate linking the genomic and phenotypic properties of the samples. Results: We introduce Efficient VIsual analytics tool for Data ENrichment in phylogenetic TreEs (Evidente), a web-application that provides an interactive visual analysis interface for the simultaneous interrogation of phylogenetic relationships, genome-wide SNP data and metadata for samples of an organism. Besides visualizing the phylogenetic tree, Evidente classifies SNPs as supporting or non-supporting of the tree structures and shows the distribution of both types of SNPs among samples and clades of interest. Furthermore, additional metadata can be included in the visualization. Lastly, Evidente includes an enrichment analysis to identify over-represented genomic features encoded by GO-terms within the clades of the tree. We demonstrate the usability of Evidente with the data of the pathogens Availability and implementation: Evidente is available at the TueVis visualization web server at https://evidente-tuevis.cs.uni-tuebingen.de/, it can also be run locally. Supplementary information: Supplementary data are available at
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Registered trials
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