Advances in Genome Biology and Technology (AGBT)

Ingenuity Demo Suite: Lanai 179

Poster Sessions: Thursday, February 21st, 7:00 am – 9:00 am

Poster Number: 214

Poster Presenter: Dan Richards, Vice President, Biomedical Informatics, Ingenuity

Title: Rapid Identification of Clinically Relevant Variants from Human Sequencing Data

Abstract: Biological interpretation of thousands of potentially deleterious variants is a bottleneck in discovering valuable causal insights from DNA resequencing studies, often requiring months of effort after completion of the variant calling step. Ingenuity® Variant Analysis (www.ingenuity.com/variants) is an application that leverages an extensive knowledge base of millions of expert-curated mutation and biomedical findings from the literature and integrated reference information to enable real-time interactive filtering and rapid prioritization of variants. We have extended it to compute a synthesis of the current knowledge about variants to provide automated initial clinical assessments. Aside from empowering clinical researchers to immediately identify reportable variants in medical genomes, we have optimized gene-level burden tests on the order of 100x faster than conventional methods while delivering consistent results, and pathway level causally-consistent algorithms to find the few variants that are most compelling for follow-up in multi-sample studies. Using a combination of causal analytics, statistical and genetic analysis at the variant, gene, and pathway levels, and the ability to visualize how variants impact disease progression, we will demonstrate the application of a context-rich knowledge base to discover clinically relevant cancer driver variants and novel causal variants for human genetic disease.

Customer Talk: Thursday, February 21st, 7:50 pm – 8:10 pm

Presenter: Gustavo Glusman, Institute for Systems Biology

Title: Multi-Genome Analysis: a Crucual Tool for Clinical Genomics

Abstract: The Family Genomics group (familygenomics.systemsbiology.net) at the Institute for Systems Biology has undertaken multiple collaborative projects related to understanding the genetic basis of disease, with special emphasis on neurodegeneration. We currently have high quality whole-genome sequence (WGS) data from 600 individuals, produced by Complete Genomics, and funded by the University of Luxembourg (wwwen.uni.lu/lcsb). We analyze the data using custom workflows and the Ingenuity Variant Analysis platform (www.ingenuity.com/variants).

In addition to powering discovery of disease-causing variants, this data set is an extraordinary resource for learning more about the genome. For example, inheritance state analysis of many pedigrees enables the identification of both common and family-specific hotspots of recombination. In a clinical context, false negatives and false positives constitute a pressing challenge for WGS technologies and analyses. Our collective WGS dataset serves as a superb resource for modeling systematic failures and biases in the technology. Such models strongly improve our ability to analyze each individual genome. Two examples follow. • Median Coverage Profiles created from several hundred genomes permit normalization of the coverage profiles of individual genomes. This enables precise analysis of CNVs and the identification of large deletions that were previously undetectable.

Some of the deletions we discovered explain the observed pattern of disease inheritance in the families we are studying. • When analyzing personal genomes, certain genes (like titin, mucins, olfactory receptor genes) frequently show up as mutated candidates most likely to be false positives. Instead of ignoring them, we have defined a set of >30,000 Commonly Mutated Segments that allow for a more fine-grained filtering of problematic regions. We make available several resources for improving the quality of personal genome analyses. The resulting improvements to sensitivity and specificity are crucial for achieving clinical-grade genome interpretation.

About AGBT

The 14th annual Advances in Genome Biology and Technology (AGBT) meeting will be held in Marco Island, Florida, on February 20-23, 2013. Now productively entrenched within the genomics research community, this annual meeting is the most rigorous scientific forum for acquiring information about the latest advances in DNA sequencing technologies and their myriad applications. Following a well-established routine, the meeting will have daytime plenary sessions that feature keynote speakers, additional invited presenters, and abstract-selected talks. These sessions will highlight cutting-edge research across the expanding landscape of genomics research. Experimental and computational approaches for effectively utilizing the latest DNA sequencing technologies will be presented during evening concurrent sessions.

The 2013 meeting will see an increased emphasis on clinical applications of genome sequencing. We especially encourage scientists who are currently active in the clinical diagnostics field to register for the meeting and to submit abstracts. Our plenary sessions will include speakers with expertise in applying next-generation sequencing in the clinical setting.

Please plan to join us in Marco Island for the 2013 AGBT meeting, where the relaxed atmosphere and outstanding science will again provide an exceptional opportunity to meet and interact with scientific leaders from the various disciplines being advanced by large-scale DNA sequencing and genome exploration.

The organizing committee for the 2013 AGBT meeting includes Eric Green (NHGRI/NIH), Elaine Mardis (Washington University School of Medicine), Deanna Church (NCBI/NIH), Ken Dewar (McGill University and Génome Québec Innovation Centre), George Grills (Cornell University), Andre Marziali (University of British Columbia), John McPherson (Ontario Institute for Cancer Research), Len Pennacchio (Lawrence Berkeley National Laboratory), Sharon Plon (Baylor College of Medicine), Heidi Rehm (Partners Healthcare Center for Personalized Genetic Medicine), Mike Zody (Broad Institute of MIT and Harvard).

For more information go to http://agbt.org/