treesapp

TreeSAPP: Tree-based Sensitive and Accurate Phylogenetic Profiler

Overview

TreeSAPP is a python package for functional and taxonomic annotation of proteins from genomes and metagenomes using phylogenetic placement.

Quick start

We recommend installing TreeSAPP into its own conda environment with the following command:

conda create -n treesapp_cenv -c bioconda -c conda-forge treesapp
conda activate treesapp_cenv

To list all the sub-commands run treesapp.

To test the assign workflow, run:

treesapp assign -i TreeSAPP/tests/test_data/marker_test_suite.faa -m prot --trim_align -o assign_test -t McrA,DsrAB

To classify sequences in your genome of interest:

treesapp assign -i my.fasta -o ~/path/to/output/directory/

TreeSAPP comes installed with 33 reference packages involved in a variety of biogeochemical and cellular processes. We also have many more reference packages available on our RefPkgs repository and you can view the complete list here.

Tutorials

All of our tutorials are available on the GitHub wiki page. Here are some specific tutorial examples:

If we do not yet have a reference package for a gene you are interested in, please try building a new reference package. Of course, if you run into any problems or would like to collaborate on building many reference packages don't hesitate to email us or create a new issue with an 'enhancement' label.

To determine whether the sequences used to build your new reference package are what you think they are, and whether it might unexpectedly annotate homologous sequences, see the purity tutorial.

If you are working with a particularly complex reference package, from an orthologous group for example, or have extra phylogenetic information you'd like to include in your classifications, try annotating extra features with treesapp layer.

Citation

If you found TreeSAPP useful in your work, please cite the following paper:

Morgan-Lang, C., McLaughlin, R., Armstrong, Z., Zhang, G., Chan, K., & Hallam, S. J. (2020). TreeSAPP: The Tree-based Sensitive and Accurate Phylogenetic Profiler. Bioinformatics, 1–8.

This was brought to you by the team:

• Connor Morgan-Lang (cmorganl, maintainer)
• Ryan McLaughlin (McGlock)
• Grace Zhang (grace72)
• Kevin Chan (kevinxchan)
• Zachary Armstrong
• Steven J. Hallam

References

If you're feeling extra citation-happy, please consider citing the following works as well:

• Eddy, S. R. (1998). Profile hidden Markov models. Bioinformatics (Oxford, England), 14(9), 755–763.
• Criscuolo, A., & Gribaldo, S. (2010). BMGE (Block Mapping and Gathering with Entropy): A new software for selection of phylogenetic informative regions from multiple sequence alignments. BMC Evolutionary Biology, 10(1).
• Kozlov, A. M., Darriba, D., Flouri, T., Morel, B., & Stamatakis, A. (2019). RAxML-NG: a fast, scalable and user-friendly tool for maximum likelihood phylogenetic inference. Bioinformatics, 35(21), 4453–4455.
• Barbera, P., Kozlov, A. M., Czech, L., Morel, B., & Stamatakis, A. (2018). EPA-ng: Massively Parallel Evolutionary Placement of Genetic Sequences. Systematic Biology, 0(0), 291658.