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  • Introduction
  • Considering the digital universe of data to better diagnose and treat patients
  • An Integrative Omics Approach
  • Leveraging Predictive Network Models to Drive Personalized Cancer Therapy
  • Example Case: Glioblastoma Multiforme
  • Patient mutation data projected onto the network: Interesting 1000-node subnetwork identified
  • Chemigenomics Screen
  • More functional chemigenomics screen: Chemical perturbagens against tumors in silico
  • Some drugs show enrichment patterns increasing towards patient key drivers
  • What we’ve noticed: non-protein coding mutations are key drivers and most often alter genes that are not TFs or signaling molecules
  • We have previously demonstrated the ability of PacBio SMRT sequencing (long reads one of the hallmarks) to complete genomes
  • …and demonstrated utility of long reads to organize mutation information from tumors to validate targets and identify resistance haplotypes
  • Icahn Institute for Genomics and Multiscale Biology at Mount Sinai School of Medicine
  • To get to comprehensive hybrid panels we generated 10-15x coverage of human genome NA12878 (from CEPH)
  • What we’ve noticed: non-protein coding mutations are key drivers and most often alter genes that are not TFs or signaling molecules
  • HTT gene TNRs Associated with HD in NA12878
  • CACNA1A gene TNRs Associated with Spinocerebellar Ataxia 6 in NA12878
  • But what about the unexplored structural variants across the genome?
  • Covered ~84% of the 10K tandem repeats > 150bp
  • Structural Variations in the MHC Region (32746700-32751000) The good (straightforward)
  • More MHC SV: The bad (far less straightforward)
  • Repeat-heavy region of chromosome 22: 18,650,000-18,900,000
  • Low complexity regions with high ILMN and 454 coverage
  • Multiple Pacbio contigs map to this region
  • Focusing SMRT sequencing on human DNA: Moving into the clinic with a hybrid sequencing approach
  • Acknowledgements
  • Q&A 1
  • Q&A 2
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  • Speaker: Eric Schadt, PhD / Icahn School of Medicine at Mount Sinai
  • Speaker: Eric Schadt, PhD / Icahn School of Medicine at Mount Sinai
  • Speaker: Eric Schadt, PhD / Icahn School of Medicine at Mount Sinai
  • Speaker: Eric Schadt, PhD / Icahn School of Medicine at Mount Sinai
  • Speaker: Eric Schadt, PhD / Icahn School of Medicine at Mount Sinai
  • Speaker: Eric Schadt, PhD / Icahn School of Medicine at Mount Sinai
  • Speaker: Eric Schadt, PhD / Icahn School of Medicine at Mount Sinai
  • Speaker: Eric Schadt, PhD / Icahn School of Medicine at Mount Sinai
  • Speaker: Eric Schadt, PhD / Icahn School of Medicine at Mount Sinai
  • Speaker: Eric Schadt, PhD / Icahn School of Medicine at Mount Sinai
  • Speaker: Eric Schadt, PhD / Icahn School of Medicine at Mount Sinai
  • Speaker: Eric Schadt, PhD / Icahn School of Medicine at Mount Sinai
  • Speaker: Eric Schadt, PhD / Icahn School of Medicine at Mount Sinai
  • Speaker: Eric Schadt, PhD / Icahn School of Medicine at Mount Sinai
  • Speaker: Eric Schadt, PhD / Icahn School of Medicine at Mount Sinai
  • Speaker: Eric Schadt, PhD / Icahn School of Medicine at Mount Sinai
  • Speaker: Eric Schadt, PhD / Icahn School of Medicine at Mount Sinai
  • Speaker: Eric Schadt, PhD / Icahn School of Medicine at Mount Sinai
  • Speaker: Eric Schadt, PhD / Icahn School of Medicine at Mount Sinai
  • Speaker: Eric Schadt, PhD / Icahn School of Medicine at Mount Sinai
  • Speaker: Eric Schadt, PhD / Icahn School of Medicine at Mount Sinai
  • Speaker: Eric Schadt, PhD / Icahn School of Medicine at Mount Sinai
  • Speaker: Eric Schadt, PhD / Icahn School of Medicine at Mount Sinai
  • Speaker: Eric Schadt, PhD / Icahn School of Medicine at Mount Sinai
  • Speaker: Eric Schadt, PhD / Icahn School of Medicine at Mount Sinai
  • Speaker: Eric Schadt, PhD / Icahn School of Medicine at Mount Sinai
  • Speaker: Eric Schadt, PhD / Icahn School of Medicine at Mount Sinai
  • Speaker: Eric Schadt, PhD / Icahn School of Medicine at Mount Sinai