GenomExplorer - genomic cancer data visualization

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Brief Description: The purpose of this project is to provide a mechanism for visualizing genomic data by means of a web based application leveraging Asynchronous Javascript and XML (AJAX) technology. We expect this tool to allow us to visualize End-sequence Profiling (ESP) data from multiple genomes in order to facilitate the detection of common rearrangements which can later be validated in the lab.

Participating Labs: Collins Lab at UCSF Cancer Center

Research Purpose: Tumor genomes can be highly rearranged and, thus may not be co-linear with host genome. Recurrent genome rearrangements involve genes that mediate a wide range of growth and signaling pathways that are increasingly targeted by anti-tumor therapeutics. Current technologies for studying tumor genome structure are not capable of elucidating the structural organization of tumor genomes at high resolution, or of relating it to the underlying host sequence. Consequently, the role of translocations and inversions in solid tumors is poorly understood. Indeed, even the structural organization of amplicons remains largely enigmatic. End Sequence Profiling (ESP) is a sequence-based method for directly determining the structural organization of tumor genomes, and for cloning all types of structural rearrangements en masse. In addition, ESP can be carried out on tumor transcriptomes for large-scale identification of fusion transcripts. We have demonstrated this by analyzing full length enriched and normalized cDNA libraries from MCF7 (breast cancer), LnCaP (prostate cancer), and a primary brain tumor. Multiple tumor-specific transcripts were identified and analyzed. The sheer amount and diversity of the data generated by ESP necessitate development of efficient and effective way to visualize and compare ESP genomic and transcriptome data. The purpose of this project, GenomExplorer, is to provide a mechanism for visualizing ESP data by means of a web based application leveraging Asynchronous Javascript and XML (AJAX) technology. We expect this tool to allow us to visualize ESP data from multiple genomes in order to facilitate the detection of common rearrangements which can later be validated in the lab.

Publications

Poster Presentations

• Accepted for presentation at the First Annual RECOMB Satellite Workshop on Computational Cancer Biology during Tuesday-Thursday September 18-20, 2007

Software

• In Progress

Research Team

• Collins Lab at UCSF Cancer Center
  • Colin Collins, Ph. D., Principal Investigator
  • Stanislav Volik, Ph.D., Researcher
• SFSU
  • Ilmi Yoon, Ph.D. Principal Investigator, Primary Thesis advisor
  • Rahul Singh, Ph.D., Thesis advisor
  • Arno Puder, Ph.D., Thesis advisor
  • Emmanuel Yera, Graduate Researcher