New & Noteworthy
Changes to the SGD GAF File of Gene Ontology Annotations
March 11, 2014
The SGD Gene Associations file (GAF; gene_association.sgd) contains Gene Ontology (GO) annotations for all yeast genes, in a standard file format specified by the GO Consortium. We are changing the taxon identifier in this file to be consistent with the reference genome sequence at GenBank and protein entries at UniProt.
Until now, the taxon identifier in column 13 of SGD’s GAF has been 4932, which refers to Saccharomyces cerevisiae in general rather than to a specific S. cerevisiae strain. Starting March 8th, 2014, we have changed this to taxon ID 559292, which is specific to the S288C strain used for the S. cerevisiae reference genome sequence.
Please note that the taxon ID 559292 merely reflects the sequence (genome) to which the geneIDs in column 2 are mapped. SGD will continue to capture gene functions (GO annotations) for all strains of S. cerevisiae. Please contact us if you have any questions.
The S. cerevisiae GO annotations (GAF) can be downloaded from SGD’s Downloads site.
Categories: Data updates
YeastMine Upgrade
May 28, 2013
YeastMine, SGD’s powerful search and retrieval tool, has been upgraded to use InterMine version 1.1 software. Highlights of this release include a new format for the template results page, the addition of PantherDB and Homologene homolog data, an improved representation of Gene Ontology (GO) information, the ability to set background population within the GO enrichment widget, and an option to share lists with other users. In addition to the existing video tutorials, a new Help document describes some common queries. See an overview of these new features in the video below, New, Fun YeastMine 1.1!:
New, Fun YeastMine 1.1! from yeastgenome on Vimeo.
Categories: Data updates, New Data
Take SGD with you wherever you go!
May 07, 2012
The YeastGeome app splash screen on an iPad.
SGD has just released an app for the iPhone, iPad and iPod touch ap(p)tly called “YeastGenome”, containing the latest Saccharomyces cerevisiae information from the database, available now as a free download on iTunes. Search by gene names, gene descriptions or simply browse for quick access to Gene Ontology annotations, mutant phenotypes and protein and genetic interaction data for your favorite genes – all at your fingertips!
Use YeastGenome to:
- Search using gene name or keywords
- Browse by genomic feature types
- Save your favorite genomic features
- Quickly see fundamental genomic feature information
- Find Gene Ontology terms, Phenotypes, Interactions, and References associated with genomic features
… with or without an internet connection!
How many ATP-dependent RNA helicases is the S. cerevisiae genome known to encode? Which proteins have a zinc finger motif? Now you can answer these questions and more with the YeastGenome app, whether you’re in line at the supermarket or having lunch with your colleagues or attending a seminar with no wifi-access! Get your friends and colleagues as fired up about The Awesome Power of Yeast as you are – use YeastGenome to email information about genomic features to collaborators and spread the word!
Please read our FAQ or visit iTunes for more information.
Categories: Data updates
Filter Expression Data by Experimental Condition
December 16, 2011
Expression analysis at SGD now offers the ability to filter datasets by condition(s) or process(es) studied. A set of controlled vocabulary (CV) terms describing various perturbations associated with microarray experiments has been constructed and defined, and these terms have been used to tag the comprehensive collection of almost 400 datasets now available in SGD’s instance of SPELL (Serial Pattern of Expression Levels Locator). In this manner, datasets displayed in search results can be filtered using tags (CV terms) such as “oxidative stress” or “sporulation.” Filtering is an option for the “New Search,” “Show Expression Levels,” and “Dataset Listing” features. The SPELL interface has been provided through a collaboration with the SGD Colony at Princeton University. Special thanks to Peter Koppstein, Lance Parsons, and Kara Dolinski for help in implementing the dataset tag filtering option for SPELL at SGD.
Categories: Data updates, Website changes
GO Slims Updated
August 12, 2011
SGD has updated its Yeast Molecular Function and Biological Process GO Slims to include additional terms. The Yeast GO Slims are a set of GO terms that best represent the major biological processes, molecular functions, and cellular components that are found in S. cerevisiae. GO Slim terms are useful in mapping precise, “granular” gene annotations to more general “high-level” terms. These terms have been selected by SGD curators based on annotation statistics and biological significance. To complement the expanded Yeast GO Slims, we have also added “generic GO-Slim” options to our GO Slim Mapper tool. The generic GO-Slim is developed and maintained by the Gene Ontology Consortium and includes fewer and higher-level terms than those provided by the Yeast GO-Slim.
The Yeast GO Slims are available for analysis via the GO Slim Mapper tool and YeastMine. Mapping of all the yeast gene products to the Yeast GO Slims is also available as a graphical view on the Genome Snapshot page and via the go_slim_mapping.tab file on the downloads site.
Categories: Data updates
Textpresso now includes publications from 2011
June 21, 2011
The SGD full-text literature search (powered by Textpresso) has been upgraded and updated to include 58,000 papers. Textpresso now includes the ability to restrict your searches to a subset of PMIDs as well as limit the results to a specific section of a paper. The full-text literature search can be accessed via the Full-text Search link on the home page. Thanks to Arun Rangarajan and Hans-Michael Muller from Wormbase for their help upgrading the software.
Categories: Data updates
New Genome-wide High-throughput Data Tracks Added to GBrowse and PBrowse
June 09, 2011
We’ve added new data tracks to our GBrowse genome viewer from eight publications, including recent surveys of nucleosome occupancy and positioning (Kaplan et al., 2009; Field et al., 2008; Mavrich et al., 2008; Lee et al., 2007); ncRNAs and RNA secondary structures (Lardenois et al., 2011 and Kertesz et al., 2010); and transcription factor and RNA Pol II occupancy (Venters et al., 2011 and Mayer et al., 2010). We have also added a data track to our Pbrowse proteome browser, displaying mature N-termini of mitochondrial proteins as determined by Vögtle et al., 2009. Both GBrowse and PBrowse have been upgraded to the most recent software with several new features.
We invite authors to work with us to integrate their data into our GBrowse and PBrowse viewers pre- and/or post-publication as we move forward. Watch for the regular addition of new tracks to SGD’s GBrowse and PBrowse in the future! Please contact us if you are interested in participating or have questions and comments.
Categories: Data updates, New Data
New Expression Analysis Tool and Datasets
February 23, 2011
Expression analysis at SGD has a new powerful interface and many new datasets. The new interface uses a tool called SPELL (Serial Pattern of Expression Levels Locator). This analysis tool facilitates the rapid identification of the most informative datasets and co-expressed genes based on patterns of expression shared with the query gene(s). By transitioning to this tool, expression data from a comprehensive collection of almost 400 datasets are now available at SGD. The expression analysis tool can be accessed via the expression tab, the expression summary histogram, and in the functional analysis pulldown located on Locus Summary pages. These new data and the SPELL interface have been provided through a collaboration with the SGD Colony at Princeton University. Thanks to Peter Koppstein, Lance Parsons, and Kara Dolinski for help with data preparation and implementation of SPELL at SGD. SPELL was developed by the Troyanskaya lab at Princeton University (Hibbs et al. (2007) Bioinformatics 23:2692).
Categories: Data updates, Website changes