JBrowse: a next-generation genome browser.

We describe an open source, portable, JavaScript-based genome browser, JBrowse, that can be used to navigate genome annotations over the web. JBrowse helps preserve the user's sense of location by avoiding discontinuous transitions, instead offering smoothly animated panning, zooming, navigation, and track selection. Unlike most existing genome browsers, where the genome is rendered into images on the webserver and the role of the client is restricted to displaying those images, JBrowse distributes work between the server and client and therefore uses significantly less server overhead than previous genome browsers. We report benchmark results empirically comparing server- and client-side rendering strategies, review the architecture and design considerations of JBrowse, and describe a simple wiki plug-in that allows users to upload and share annotation tracks.

Setting up the JBrowse genome browser.

JBrowse is a Web-based tool for visualizing genomic data. Unlike most other Web-base genome browsers, JBrowse exploits the capabilities of the user's Web browser to make scrolling and zooming fast and smooth. It supports the browsers used by almost all Internet users, and is relatively simple to install. JBrowse can utilize multiple types of data in a variety of common genomic data formats, including genomic feature data in bioperl databases, GFF files, BED files, and quantitative data in wiggle files. This unit describes how to obtain the JBrowse software, set it up on a Linux or Mac OS X computer running as a Web server, and incorporate genome annotation data from multiple sources into JBrowse. After completing the protocols described in this unit, the reader will have a Web site that other users can visit to browse the genomic data.

Evolutionary modeling and prediction of non-coding RNAs in Drosophila.

We performed benchmarks of phylogenetic grammar-based ncRNA gene prediction, experimenting with eight different models of structural evolution and two different programs for genome alignment. We evaluated our models using alignments of twelve Drosophila genomes. We find that ncRNA prediction performance can vary greatly between different gene predictors and subfamilies of ncRNA gene. Our estimates for false positive rates are based on simulations which preserve local islands of conservation; using these simulations, we predict a higher rate of false positives than previous computational ncRNA screens have reported. Using one of the tested prediction grammars, we provide an updated set of ncRNA predictions for D. melanogaster and compare them to previously-published predictions and experimental data. Many of our predictions show correlations with protein-coding genes. We found significant depletion of intergenic predictions near the 3' end of coding regions and furthermore depletion of predictions in the first intron of protein-coding genes. Some of our predictions are colocated with larger putative unannotated genes: for example, 17 of our predictions showing homology to the RFAM family snoR28 appear in a tandem array on the X chromosome; the 4.5 Kbp spanned by the predicted tandem array is contained within a FlyBase-annotated cDNA.