Dataset Information

Fiberweb: Diffusion Visualization and Processing in the Browser.

ABSTRACT: Data visualization is one of the most important tool to explore the brain as we know it. In this work, we introduce a novel browser-based solution for medical imaging data visualization and interaction with diffusion-weighted magnetic resonance imaging (dMRI) and tractography data: Fiberweb. It uses a recent technology, WebGL, that has yet to be fully explored for medical imaging purposes. There are currently very few software tools that allow medical imaging data visualization in the browser, and none of these tools support efficient data interaction and processing, such as streamlines selection and real-time deterministic and probabilistic tractography (RTT). With Fiberweb allowing these types of interaction, it is no longer the case. We show results of the visualization of medical imaging data, and demonstrate that our new RTT probabilistic algorithm can compare to a state of the art offline algorithm. Overall, Fiberweb pushes the boundary of interaction combined with scientific visualization, which opens great perspectives for quality control and neurosurgical navigation on browser-based mobile and static devices.

SUBMITTER: Ledoux LP

PROVIDER: S-EPMC5563309 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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Publications

Fiberweb: Diffusion Visualization and Processing in the Browser.

Ledoux Louis-Philippe LP Morency Felix C FC Cousineau Martin M Houde Jean-Christophe JC Whittingstall Kevin K Descoteaux Maxime M

Frontiers in neuroinformatics 20170818

Data visualization is one of the most important tool to explore the brain as we know it. In this work, we introduce a novel browser-based solution for medical imaging data visualization and interaction with diffusion-weighted magnetic resonance imaging (dMRI) and tractography data: Fiberweb. It uses a recent technology, WebGL, that has yet to be fully explored for medical imaging purposes. There are currently very few software tools that allow medical imaging data visualization in the browser, a ...[more]

PMID: 28868000

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Project description:BackgroundNearly half the human genome consists of repeat elements, most of which are retrotransposons, and many of which play important biological roles. However repeat elements pose several unique challenges to current bioinformatic analyses and visualization tools, as short repeat sequences can map to multiple genomic loci resulting in their misclassification and misinterpretation. In fact, sequence data mapping to repeat elements are often discarded from analysis pipelines. Therefore, there is a continued need for standardized tools and techniques to interpret genomic data of repeats.ResultsWe present the UCSC Repeat Browser, which consists of a complete set of human repeat reference sequences derived from annotations made by the commonly used program RepeatMasker. The UCSC Repeat Browser also provides an alignment from the human genome to these references, uses it to map the standard human genome annotation tracks, and presents all of them as a comprehensive interface to facilitate work with repetitive elements. It also provides processed tracks of multiple publicly available datasets of particular interest to the repeat community, including ChIP-seq datasets for KRAB Zinc Finger Proteins (KZNFs) - a family of proteins known to bind and repress certain classes of repeats. We used the UCSC Repeat Browser in combination with these datasets, as well as RepeatMasker annotations in several non-human primates, to trace the independent trajectories of species-specific evolutionary battles between LINE 1 retroelements and their repressors. Furthermore, we document at https://repeatbrowser.ucsc.edu how researchers can map their own human genome annotations to these reference repeat sequences.ConclusionsThe UCSC Repeat Browser allows easy and intuitive visualization of genomic data on consensus repeat elements, circumventing the problem of multi-mapping, in which sequencing reads of repeat elements map to multiple locations on the human genome. By developing a reference consensus, multiple datasets and annotation tracks can easily be overlaid to reveal complex evolutionary histories of repeats in a single interactive window. Specifically, we use this approach to retrace the history of several primate specific LINE-1 families across apes, and discover several species-specific routes of evolution that correlate with the emergence and binding of KZNFs.

Dataset Information

Fiberweb: Diffusion Visualization and Processing in the Browser.

Publications

Fiberweb: Diffusion Visualization and Processing in the Browser.

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