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Abstract Details

Activity Number: 389
Type: Invited
Date/Time: Tuesday, August 1, 2017 : 2:00 PM to 3:50 PM
Sponsor: Section on Statistical Graphics
Abstract #322423
Title: Extracting Insights from Genomic Data via Complex Interactive Heatmaps
Author(s): Alicia Schep*
Companies: Stanford School of Medicine
Keywords: visualization ; Interactive Visualization ; Genomics ; Epigenomics ; ChIP-seq ; RNA-seq

Visualizing functional genomics data from high-throughput assays is challenging due to the vast scale of the genome. Genome browsers facilitate interactive exploration of genomic data, but only show one region of the genome at a time. Complex heatmaps can show genomic data for many regions, samples and assays, but only show a lower resolution view of the data at each region. Individual heatmap rows are often unlabelled due to space constraints, making it difficult to quickly determine what gene or genes correspond to interesting rows. Adding interactivity to complex heatmaps can address these limitations, as tooltips and zooming enable discovery of the relevant genes or genomic regions. Additionally, elements of a heatmap can be linked through click events to more detailed visualizations of the data, such as a genome browser view with multiple detailed data tracks. We have developed an R package for making integrative, interactive visualizations of functional genomics data that can be incorporated into R Markdown reports and shiny applications, and will highlight application of the method to RNA-seq and ChIP-seq data.

Authors who are presenting talks have a * after their name.

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