Phylesystem: a git-based data store for community-curated phylogenetic estimates

Motivation: Phylogenetic estimates from published studies can be archived using general platforms like Dryad (Vision, 2010) or TreeBASE (Sanderson et al., 1994). Such services fulfill a crucial role in ensuring transparency and reproducibility in phylogenetic research. However, digital tree data files often require some editing (e.g. rerooting) to improve the accuracy and reusability of the phylogenetic statements. Furthermore, establishing the mapping between tip labels used in a tree and taxa in a single common taxonomy dramatically improves the ability of other researchers to reuse phylogenetic estimates. As the process of curating a published phylogenetic estimate is not error-free, retaining a full record of the provenance of edits to a tree is crucial for openness, allowing editors to receive credit for their work and making errors introduced during curation easier to correct. Results: Here, we report the development of software infrastructure to support the open curation of phylogenetic data by the community of biologists. The backend of the system provides an interface for the standard database operations of creating, reading, updating and deleting records by making commits to a git repository. The record of the history of edits to a tree is preserved by git’s version control features. Hosting this data store on GitHub (http://github.com/) provides open access to the data store using tools familiar to many developers. We have deployed a server running the ‘phylesystem-api’, which wraps the interactions with git and GitHub. The Open Tree of Life project has also developed and deployed a JavaScript application that uses the phylesystem-api and other web services to enable input and curation of published phylogenetic statements

Nested radiations and the pulse of angiosperm diversification: increased diversification rates often follow whole genome duplications

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/111924/1/nph13491-sup-0001-FigS1-TableS1-S2.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/111924/2/nph13491.pd

The bien r package: A tool to access the Botanical Information and Ecology Network (BIEN) database

There is an urgent need for largeâ scale botanical data to improve our understanding of community assembly, coexistence, biogeography, evolution, and many other fundamental biological processes. Understanding these processes is critical for predicting and handling humanâ biodiversity interactions and global change dynamics such as food and energy security, ecosystem services, climate change, and species invasions.The Botanical Information and Ecology Network (BIEN) database comprises an unprecedented wealth of cleaned and standardised botanical data, containing roughly 81 million occurrence records from c. 375,000 species, c. 915,000 trait observations across 28 traits from c. 93,000 species, and coâ occurrence records from 110,000 ecological plots globally, as well as 100,000 range maps and 100 replicated phylogenies (each containing 81,274 species) for New World species. Here, we describe an r package that provides easy access to these data.The bien r package allows users to access the multiple types of data in the BIEN database. Functions in this package query the BIEN database by turning user inputs into optimised PostgreSQL functions. Function names follow a convention designed to make it easy to understand what each function does. We have also developed a protocol for providing customised citations and herbarium acknowledgements for data downloaded through the bien r package.The development of the BIEN database represents a significant achievement in biological data integration, cleaning and standardization. Likewise, the bien r package represents an important tool for open science that makes the BIEN database freely and easily accessible to everyone.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/142458/1/mee312861_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/142458/2/mee312861.pd

makesamplingmatrix

This script accesses a directory, and traverses all FASTA files in it, recording the names of all taxa present in each file. Then it creates a tab-delimited file containing a matrix where the rows represent the taxa and the columns the FASTA files. The intended use is for a directory containing a set of FASTA files each corresponding to a single locus, and containing homologous sequences of that locus for different taxa. The script will record a 1 in the resulting matrix if a taxon is present in a locus file, or a 0 if not. Key point: the script does not intelligently differentiate FASTA files from other types, and it will attempt to parse any file in the directory. For this reason, you should remove all other files before you run the script. It will create (or overwrite!) a file in the passed directory called 'sampling_matrix.txt' that may be opened in any conventional spreadsheet or text-editor app. This file should be in the proper format for use in the Decisivator application. This script requires BioPython to be installed

instability_multicore.py

This script will calculate I^s scores, as described in (Hinchliff, C. E. and E. H. Roalson. 2012. Using supermatrices for phylogenetic inquiry: an example using the sedges. Systematic Biology). It requires a set of trees sharing a common set of tips, to be input as a newick file (though any format readable by dendropy should be trivial to use, just change the format in the appropriate line). It outputs a comma-delimited table containing the raw instability scores (the numerator from the right side of the equation in the referenced paper), as well as the scaled I^s scores. Taxa that move more have higher scores

Appendix_II

ML bootstrap majority rule consensus tree topologies from 300-replicate RAxML bootstrap searches using alignments 1-3 described in the text. Branch labels are bootstrap proportions

Appendix_II

ML bootstrap majority rule consensus tree topologies from 300-replicate RAxML bootstrap searches using alignments 1-3 described in the text. Branch labels are bootstrap proportions

phase1_at_nf.phy

Nucleotide data for Cyperaceae species from various markers, collected from GenBank using the software tool "phlawd". This alignment corresponds to the fully unfiltered alignment--labeled AT/NF in our manuscript

cyp_states

Latitudinal range data for all currently recognized species of Cyperaceae from Govaerts et al. (2007), World Checklist of Cyperaceae. Range data are encoded as tropical (state 1) or extratropical (state 0), and represent the position of the latitudinal midpoint of each species range, as estimated based on the geographic distribution data encoded within the World Checklist of Cyperaceae referenced above