title: ScreenTroll: a searchable database to compare genome-wide yeast screens.
abstract: Systematic biological screens typically identify many genes or proteins that are implicated in a specific phenotype. However, deriving mechanistic insight from these screens typically involves focusing upon one or a few genes within the set in order to elucidate their precise role in producing the phenotype. To find these critical genes, researchers use a variety of tools to query the set of genes to uncover underlying common genetic or physical interactions or common functional annotations (e.g. gene ontology terms). Not only it is necessary to find previous screens containing genes in common with the new set, but also useful to easily access the individual manuscript or study that classified those genes. Unfortunately, no tool currently exists to facilitate this task. We have developed a web-based tool (ScreenTroll) that queries one or more genes against a database of systematic yeast screens. The software determines which genome-wide yeast screens also identified the queried gene(s) and the resulting screens are listed in an order based on the extent of the overlap between the queried gene(s) and the open reading frames (ORFs) characterized in each individual yeast screen. In a separate list, the corresponding ORFs that are found in both the queried set of genes and each individual genome-wide screen are displayed along with links to the relevant manuscript via NIH's PubMed database. ScreenTroll is useful for comparing a list of ORFs with genes identified in a wide array of published genome-wide screens. This comparison informs users whether any of their queried ORFs overlaps a previous study in the ScreenTroll database. By listing the manuscript of the published screen, users can read more about the phenotype associated with that study. Together, this information provides insight into the function of the queried genes and helps the user focus on a subset of them.
authors.affiliation: Department of Genetics & Development, Columbia University Medical Center, New York, NY 10032, USA.
authors.forename: Peter H
authors.initials: PH
authors.lastname: Thorpe
authors.forename: John C
authors.initials: JC
authors.lastname: Dittmar
authors.forename: Rodney
authors.initials: R
authors.lastname: Rothstein
mesh_terms: D057225:Data Mining / Q000379:methods*; D003628:Database Management Systems; D016208:Databases, Factual; D005800:Genes, Fungal; D016681:Genome, Fungal; D020407:Internet; D016366:Open Reading Frames; D039781:PubMed; D012441:Saccharomyces cerevisiae / Q000235:genetics*; D014584:User-Computer Interface