OCT 05, 2016 6:00 AM PDT

Unique molecular indices (UMI) and their application in detecting novel gene fusions and gene expression and genetic variation

Speaker
  • Senior Global Product Manager, RNA Profiling , QIAGEN
    Biography
      Samuel Rulli is a Senior Global Product Manager for the QIAseq RNA Profiling Technologies at QIAGEN. Dr. Rulli received his Ph.D. in 2002 from Tulane University studying the gastric proton pump and did post-doctoral research at Johns Hopkins University and the National Cancer Institute in Frederick, MD. He joined SABiosciences - now a part of QIAGEN - in 2007 as an R&D Scientist in qPCR applications and moved to a Global Product Manager role in 2014. Trained as a molecular biologist, Dr. Rulli has worked on different assay detection technologies for gene expression and nucleic acid analysis.

    Abstract

    Tumor heterogeneity has been known for a while but quantifying heterogeneity is still a challenge.  NGS is the method of choice in the analysis of tumor heterogeneity, however, there are some inherent challenges associated with it. These include false positives, gaps in the gene due to overrepresentation and incomplete representation of low-frequency transcripts – all contributing to an inaccurate picture.  Conventional library prep strategies for NGS are based on PCR, which introduces sequence-based bias and amplification noise, leading to these inaccuracies. 

    In this webinar, we will cover

    1. Principles of UMI and the new QIAseq product porfolio
    2. How UMI along with SPE (single primer extension) allows for increased uniformity across difficult-to-sequence regions, removal of library construction bias, improved data analysis and sequencing optimization
    3. How data generated from using UMI and SPE is directly comparable to analysis derived from whole transcriptome and exome sequencing
    4. Application of UMI and SPE in the discovery of novel gene fusions and in the analysis of gene expression and genetic variation

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    OCT 05, 2016 6:00 AM PDT

    Unique molecular indices (UMI) and their application in detecting novel gene fusions and gene expression and genetic variation


    Specialty

    Cancer

    Gene Expression

    Dna

    Mass Cytometry

    Cancer Research

    T-Cells

    Biomarkers

    Immunotherapeutics

    Oncology

    Research

    Gene Sequencing

    Molecular Genetics

    Drug Discovery

    Personalized Medicine

    Cell Culture

    Geography

    Europe100%

    Registration Source

    Website Visitors100%

    Job Title

    Student100%

    Organization

    Academic Institution100%


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