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Genboree Discovery Process Integration Aleksandar Milosavljevic, PhD Baylor College of Medicine January 10 th, 2008; modified April 1 st 2008.
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Genboree design has evolved to support diverse discovery processes Authors: Gonzalez-Garay, M.L. 1,2, Morgan, M.B 2, Miller, CA 1,3, Jackson, A.R. 1,2, Tong, M. 1,2, Gibbs, R.A. 2,3, Milosavljevic, A. 1,2,3 1 Bioinformatics Research Laboratory; 2 Human Genome Sequencing Center, Department of Molecular and Human Genetics; 3 Program in Structural and Computational Biology and Molecular Biophysics, Baylor College of Medicine, Houston, Texas, USA
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Genboree design has evolved to support diverse discovery processes Genome sequencing and annotation human Ch 3, 12; sea urchin; tribolium, nasonia; bacterial Genome comparison rat, mammals, rhesus macaque, primates High-throughput microchip analysis array CGH, BCM cytogenetics laboratory DNA sequencing PCR-based resequencing; mapping rearrangements in cancer genomes using next generation sequencing technologies
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Genboree software development Understanding of user’s needs and opportunities Focus on complete process Identify recurrent use patterns Generalize, minimize assumptions for widest use Design generic components for reuse across projects Fast prototyping Frequent feedback Extensive optimization of key components
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Usage of Genboree.org as of Dec 31 2007 923 registered users ~100 users each working day ~10,000 clicks per day 112 collaborating groups with 2+ researchers, with a median of 7 and average of 23.5 members per group many collaborating groups still maintain private access to their pre-publication data and 23 databases have been made widely accessible via internet by the collaborating groups
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Genboree’s current focus: Translational studies of genome variation
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Example 1: research at the clinical cytogentics laboratory at BCM Agilent array design for array CGH (version 7): identifying hypermutable Low Copy Repeat regions for deeper probing Analysis of a single case Upload Agilent array data Perform segmentation (invoke Bioconductor tool) Subtract polymorphisms (databases, current literature) Establish preliminary diagnosis/ hypothesis Integrate downstream data ( paternal testing, FISH, etc.) Share diagnosis and data view with reporting physician Identify recurrent events (based on BCM database) Identify new syndromes
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Translational studies of genome variation High volume anchoring (by Pash 2.0) integrated with Genboree
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Genboree overview
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Integration of Genboree into caBIG infrastructure and caGRID Current state Integrated state
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Example 3: Pilot TCGA pilot project Target selection ( Target Selection Group, Mr. Chris Miller, Dr. Anna Lapuk) Data integration (Level 3,4 data) Collaborative target selection Target allocation across centers (Manuel) PCR assay design: integration with the HGSC LIMS system for probe design; hole filling, polymorphisms, repeats, tiling (Dr. Manuel Gonzalez-Garay) Quarterly Report for PCR resequencing (Dr. Manuel Gonzalez-Garay) ( Mutation annotation, sharing of PCR assays, prioritization of mutations for collaborative downstream studies )
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Project view TCGA Project – Quarterly Resequencing Report Keyword Search: Sample Completion Table Gene Completion Table Amplicon Completion Table Genome view Annotation object - viewer - editor - PCR primer designer - other tools
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Annotation object (Mutation) view TCGA Project – Quarterly Resequencing Report Genome view
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Key challenge: lowering threshold to adoption of genomic technologies by clinical researchers Key challenge: Integration of discovery processes. -> Integration of data and tools required but not sufficient. Genboree follows internet-based hosting model (Software as a Service). -> No installation, maintenance, needed. -> Open source release in Q2 2008. -> Commercial launch of the Genboree Early Access Hosting program ( www.genboree.com ) on March 1 st 2008.www.genboree.com
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