BBISR "Do it Yourself" Workshop Series: Survival Analysis - Using Cancer Survival Analysis Suite (CASAS)

  • Online Registration
  • Date
    - Add to Calendar
  • Location
    Bioinformatics & Biostatistics Shared Resource at Winship
    718 Gatewood Road NE Atlanta, Georgia 30329
  • Event Type

    Lectures and Training

  • Description

    The Bioinformatics & Biostatistics Shared Resource (BBISR) at Winship Cancer Institute is hosting a series of ‘do it yourself’ workshops.  The intent of the workshops is to introduce biostatistics and bioinformatics application tools for cancer research, and to equip investigators with tools to enable efficient data mining that will help in formulating specific research questions to address with the BBISR team. Each workshop will provide detailed instruction on the use of the specific tool presented in addition to informing on the guiding principles behind it. All application tools developed by the BBISR can be accessed directly from the BBISR website.

    Workshop participants must bring their own laptops to the workshop and are encouraged to bring their own data, in addition to the supplied data. The number of participants in each workshop is limited to 10. You must pre-register by May 15.

     

  • Details

    BBISR "Do it Yourself" Workshop Series: Survival Analysis - Using Cancer Survival Analysis Suite (CASAS)

    Friday, June 30, 1:00 pm - 3:30 pm
    718 Gatewood Rd. NE, Atlanta GA 30329

    There is no parking at this location. Please use the Emory shuttle or walk. If you drive, you'll have to pay to park at the Michael Street deck (550 Houston Mill Road, Atlanta, 30322.)

    Survival analysis in cancer research is one of the most fundamental analysis methods, answering the frequent question of whether a marker is associated with overall survival.  We dive deeper into this question by testing marker associations  that occur ‘early’ vs. later vs. a landmark start time.

    With CASAS, you can use:

    • Any data set with survival information

    With CASAS, you can define:

    • Markers associated with survival starting with either a ‘landmark’ time or ‘early on’ post treatment
    • Several gene associations for single cancer type or several cancer types associations  for a single gene  
    • Statistical significance of a prognostic signature