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Vinh Tran edited this page Apr 12, 2019 · 10 revisions

Welcome to PhyloProfile, a tool for integrating, visualizing and exploring multi-layered phylogenetic profiles.

With PhyloProfile you can integrate up to two additional information layers into the traditional presence/absence phylogenetic profile. With the support of several kinds of input formats, users can choose their best way to prepare the required information for PhyloProfile.

The tool allows dynamically changing the resolution of the analysis by subsetting input genes/taxa or collapsing input taxa into a higher taxonomic rank. You can filter the data by applying different threshold for the integrated information layers in order to vary the stringency of the analysis.

PhyloProfile is implemented with several analysis functions, such as profile clustering, gene age estimation, core gene identification and distribution analysis. Beside the main information of the phylogenetic profiles, the tool can also optionally display FASTA sequences and the protein domain architectures.

PhyloProfile is a fully interactive visualization tool, which enable an informative exploration of phylogenetic profiles. All graphics in the tool are interactable and modifiable using various apperance configuration options.

All plots and filtered data can be downloaded for downstream anaylsis.

Click for the full PDF version of the poster

If you just want to dive in and try PhyloProfile, there is an online version that you can use. (Please check the limitation of the online version in the performance test).

The complete ability and functionality of PhyloProfile are described in the Walkthrough slides or summerized in the Functionality Page.

Check the installation help if you want to run PhyloProfile on your own machine. We additionally offer some overview on how to format your own data to visualize and analyze it with PhyloProfile.

Things don't work as you expect? Check our FAQ to get an idea what could have gone wrong. This couldn't solve your problem? Please open an issue on GitHub or contact us via email at tran@bio.uni-frankfurt.de.

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