Cambridge Healthtech Institute’s Third Annual
Genomic Data Analysis and Interpretation
Turning Data into Knowledge
March 5-7, 2012| Hilton San Diego Resort | San Diego, California
The emergence and explosion of high-throughput genomic platforms, from microarrays, quantitative PCR, mass spec, and sequencing platforms have resulted in an extraordinary output of genomic data. Thus, the ability to analyze and interpret the data has rapidly become the rate limiting step. Cambridge Healthtech Institute’s Genomic Data Analysis and Interpretation combines unique perspectives from biological researchers, biostatisticians, and software developers, creating a common ground on which to explore how best to manage, analyze, and interpret datasets. This team of scientists will reference case studies as they provide a forum to discuss recent trends and issues in the arena of genomic data analysis, integration, and interpretation.
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MONDAY, MARCH 5
8:30 am Pre-Conference Short Course Registration
9:00 am-12:00 pm Recommended Pre-Conference Short Courses*
SC1: Epigenetics Toolbox SC2: Sequencing 101
*Separate registration required.
12:00 - 2:00 pm Main Conference Registration
2:00 Chairperson's Remarks
Jennifer Hogan, Ph.D., Vice President, Product Management, BIOBASE
» 2:10 Featured Speaker:
A Genetic Survival Network for Glioblastoma Multiforme
Desmond J. Smith, Ph.D., Professor, Molecular and Medical Pharmacology, University of California, Los Angeles
To construct a survival network for glioblastoma multiforme,we identified correlated patterns of copy number alterations (CNAs) for distant genes using data from 301 tumors. We were able to obtain single gene specificity in the cancer network and found 46 genes in the glioblastoma network that showed significant interactions with the epidermal growth factor receptor (EGFR) oncogene. This observation suggests that a flank attack strategy that strikes at both EGFR and its partner genes may be an effective approach to treatment of glioblastoma.
2:45 Bioinformatics for Copy Number Detection and Assessing the Impact of Genetic Variation on Gene Regulation
Roger Pique-Regi, Ph.D., Research Scientist, Department of Human Genetics, University of Chicago
Identification of copy number alteration and its potential impact in altering gene expression is a challenging problem that requires new and more sophisticated methods. New high-throughput experimental platforms offer the means for very high-resolution scans in large cohorts of samples to study human diseases. Insights into the utilization and detection capabilities of experimental platforms will be discussed.
3:20 Assigning Functional Significance to Human Genome Variations
Jennifer Hogan, Ph.D., Vice President, Product Management, BIOBASEHigh-throughput sequencing enables a closer look at the mutations causing inherited disease and cancer than ever before, but with 3-4 million variants identified per genome it becomes a challenge to determine which count. We describe Genome Trax™, an important tool for mapping variants to published genomic features.
3:35 Networking Refreshment Break
4:00 Stepping Outside the Exome
Srinka Ghosh, Ph.D., Senior Bioinformatics Applications Manager, Complete Genomics
Chromohe landscape of DNA variation is complex, interspersed with SNPs, insertions,deletions and substitutions. Copy number and structural variants add another layer of genomic diversity. Stepping outside the exome is equal to exploring the genome without a map and compass. It is through whole genome sequencing that the evolution of a tumor genome can be understood or discoveries of rare causative variants can be made.
4:35 Inferring Causal Genomic Alterations in Breast Cancer Using Gene Expression Data
Linh M. Tran, Ph.D., Research Scientist, Molecular and Medical Pharmacology, University of California, Los Angeles
Many valuable studies lack genomic data to detect CNV; therefore, methods that are able to infer CNVs from gene expression data would help maximize the value of these studies. In this talk, we present an algorithm that systematically identifies first altered cancer genomic regions and then their causal driver genes using gene expression data.
5:10 Complex Structural Re-Arrange-ments and Somatic Copy Number Alterations Identified in Pediatric Cancer Genomes
Jinghui Zhang, Ph.D., Associate Member, Biotechnology and Computational Biology, St. Jude Children's Research Hospital
Chromosomal re-arrangements and copy number alterations are key somatic lesions contributing to cancer initiation and progression. To identify these gross somatic lesions in the Next-generation sequencing data at base-pair resolution, we developed two novel computational methods, CREST for structural variation and CONSERTING for copy number alteration. We have uncovered complex structural variations that arise by different mechanisms, and we were able to infer chronological order of gross somatic alterations and sequence mutations based on allelic imbalance in regions of structural alterations.
5:45 Close of Day
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