PCI Genomics

167

Title *

EukProt: A database of genome-scale predicted proteins across the diversity of eukaryotesuse asterix (*) to get italics

Authors *

Daniel J. Richter, Cédric Berney, Jürgen F. H. Strassert, Yu-Ping Poh, Emily K. Herman, Sergio A. Muñoz-Gómez, Jeremy G. Wideman, Fabien Burki, Colomban de VargasPlease use the format "First name initials family name" as in "Marie S. Curie, Niels H. D. Bohr, Albert Einstein, John R. R. Tolkien, Donna T. Strickland"

Year *

2022

Picture *

Abstract *

<p style="text-align: justify;">EukProt is a database of published and publicly available predicted protein sets selected to represent the breadth of eukaryotic diversity, currently including 993 species from all major supergroups as well as orphan taxa. The goal of the database is to provide a single, convenient resource for gene-based research across the spectrum of eukaryotic life, such as phylogenomics and gene family evolution. Each species is placed within the UniEuk taxonomic framework in order to facilitate downstream analyses, and each data set is associated with a unique, persistent identifier to facilitate comparison and replication among analyses. The database is regularly updated, and all versions will be permanently stored and made available via FigShare. The current version has a number of updates, notably ‘The Comparative Set’ (TCS), a reduced taxonomic set with high estimated completeness while maintaining a substantial phylogenetic breadth, which comprises 196 predicted proteomes. A BLAST web server and graphical displays of data set completeness are available at <a href="http://evocellbio.com/eukprot/" target="_blank" rel="noopener">http://evocellbio.com/eukprot/</a>. We invite the community to provide suggestions for new data sets and new annotation features to be included in subsequent versions, with the goal of building a collaborative resource that will promote research to understand eukaryotic diversity and diversification.</p>

Indicate the full web address (DOI or URL) giving public access to these data (if you have any problems with the deposit of your data, please contact contact@genomics.peercommunityin.org). In case all raw data are included in the preprint, indicate the DOI or URL of the preprint. *

https://doi.org/10.6084/m9.figshare.12417881, http://evocellbio.com/eukprot/You should fill this box only if you chose 'All or part of the results presented in this preprint are based on data'. URL must start with http:// or https://

Indicate the full web address (DOI or URL) giving public access to these scripts (if you have any problems with the deposit of your scripts, please contact contact@genomics.peercommunityin.org). In case all raw scripts are included in the preprint, indicate the DOI or URL of the preprint. *

https://doi.org/10.5281/zenodo.7025267, https://github.com/beaplab/EukProtYou should fill this box only if you chose 'Scripts were used to obtain or analyze the results'. URL must start with http:// or https://

Indicate the full web address (DOI, SWHID or URL) giving public access to these codes (if you have any problems with the deposit of your codes, please contact contact@genomics.peercommunityin.org). In case all raw codes are included in the preprint, indicate the DOI or URL of the preprint. *

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Keywords (optional)

eukaryotes, eukaryotic diversity, transcriptomes, genomes, single-cell genomes, phylogenomics, UniEuk taxonomy, predicted proteins

Methods that require specific expertise (optional)

NonePlease indicate the methods that may require specialised expertise during the peer review process (use a comma to separate various required expertises).

Thematic fields *

Bioinformatics, Evolutionary genomics

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Submission date

2022-06-08 14:19:28

Recommender

Gavin Douglas

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