WaspAtlas A Nasonia vitripennis gene database

Welcome to WaspAtlas

What WaspAtlas is

WaspAtlas is a Nasonia vitripennis gene database, which combines data from all available Nasonia vitripennis genome annotations to provide a gene-based view of the genome (for links to the original datasets used in WaspAtlas, please visit the references section). We provide easy to navigate graphical representations of transcript data, sequences, protein products, GO annotations, PFAM protein domain predictions, expression data, gene methylation data, and more. WaspAtlas uses mappings (more information) to make identifiers from different gene annotations co-navigable, and allowing data from empirical studies using any annotation dataset to be viewed on the same page. We also provide a set of tools for working with N. vitripennis, currently including RNAi off-target prediction, and gene ontology/PFAM domain hypergeometric overrepresentation tests.

As WaspAtlas allows for the integration of empirical data relating to each gene, we encourage authors of such work to submit their data to WaspAtlas so that it may be made easily available to the scientific community. Several RNA-seq datasets have already been integrated into WaspAtlas, as well as an RRBS methylation dataset and a tiling microarray dataset showing expression during development in females. We at the Tauber lab also intend to integrate our own data into the website, including methylation and expression (RNA-seq and in-situ hybridisation) data.

Please e-mail any comments or issues to etaubersdfsdfsd@univ.haifa.ac.il. Accuracy and reliability of data integrated into WaspAtlas depends on the accuracy and reliability of the original data; for questions about this this please see disclaimers attached to the original data sets. We assume no responsibility or liability for any loss or damage incurred as a result of any use of the information contained within or downloaded from this website.

For citation:
Nathaniel J. Davies and Eran Tauber
WaspAtlas: a Nasonia vitripennis gene database and analysis platform
Database 2015: bav103 doi:10.1093/database/bav103 published online October 9, 2015