PT  - JOURNAL ARTICLE
AU  - Sol Shenker
AU  - Eric Lai
TI  - <em>Crossbrowse</em>: A versatile genome browser for visualizing comparative experimental data
AID  - 10.1101/272880
DP  - 2018 Jan 01
TA  - bioRxiv
PG  - 272880
4099  - http://biorxiv.org/content/early/2018/02/28/272880.short
4100  - http://biorxiv.org/content/early/2018/02/28/272880.full
AB  - The recent beyond-exponential growth in diverse collections of deep sequencing datasets creates enormous opportunities for discovery, concomitant with new challenges for displaying and interpreting these data. Notably, the availability of scores of whole genome sequences in multiple species clades enables comparative studies of functional elements. However, current genome browsers do not permit effective visualization of multigenome experimental data. Here, we present CrossBrowse, a standalone desktop application for displaying and browsing cross-species genomic datasets. We utilize data standards and graphic representation of popular browsers, and incorporate an intuitive graphical visualization of genome synteny that facilitates and drives human interrogation of comparative data. Our platform permits users with minimal informatics capacity to select arbitrary sets of genomes for display, upload and configure multiple datasets, and interact with vertebrate-sized genomic datasets in real-time. We illustrate the utility of CrossBrowse with interrogation of comparative invertebrate and mammalian datasets that provide insights into diverse aspects of transcriptional and post-transcriptional regulation. Of note, we show examplars of both preservation and divergence of functional elements that cannot be inferred from sequence alignments alone. Moreover, we demonstrate how inspection of primary data using CrossBrowse exposes an artifact in a typical strategy for assigning species-specific functional elements, and drives the implementation of an improved computational strategy. We anticipate that CrossBrowse will greatly foster user-based discovery within multispecies genomic datasets, and inform their bioinformatic interpretation.