Biostatistics Courses Taught by Maureen Sartor

BIOSTAT606: Introduction to Biocomputing

  • Graduate level
  • Fall term(s)
  • 1 Credit Hour(s)
  • Instructor(s): Boehnke, Michael L; Grant, Barry; Jiang, Hui; Kang, Hyun Min; Kidd, Jeff; Kitzman, Jacob; Mills, Ryan; Sartor, Maureen;
  • Prerequisites: Graduate Standing
  • Description: This short course introduces basic computational environments and tools to graduate students with limited prior experience. It will provide an introduction to UNIX systems, software compilation / installation, cluster job management as well as data formats, management, and visualization. A brief introduction to scripting programming languages will also be presented.
  • Course Goals: Students enrolled in the class will develop skills to accelerate their research in computational research environments. Topics will include an intensive introduction to (a) UNIX systems and software management, (b) data processing and simple programming, (c) data formats and visualization, and (d) software version and cluster control. This training will provide a computational foundation that will allow students to focus on the theoretical and biological aspects of their research.
  • Competencies: After completing this class, students are expected to be able to attain the following competencies: Core Competencies: -Navigate and organize UNIX files and folders -Compile and install software in UNIX environments -Understand basic programming data structures and processes -Create simple scripts to manage and analyze data -Utilize and apply popular file formats to modern large-scale data sets -Apply proper visualization tools and strategies to view data -Utilize software versioning technologies for documenting and organizing software -Utilize high-throughput computing clusters for parallel data processing
  • This course is cross-listed with Biostat 606 = HG 606 = Bioinfo 606.
  • Syllabus for BIOSTAT606

BIOSTAT646: High Throughput Molecular Genetic and Epigenetic Data Analysis

  • Graduate level
  • Winter term(s)
  • 3 Credit Hour(s)
  • Instructor(s): Sartor, Maureen; Tsoi, Alex;
  • Prerequisites: Graduate Standing and STAT400, BIOSTAT522, or BIOSTAT521 or permission of instructor
  • Description: The course will cover statistical methods used to analyze data in experimental molecular biology. The course will primarily cover topics relating to gene expression data analysis, but other types of data such as genome sequence and epigenomics data that is sometimes analyzed in concert with expression data will also be covered.
  • Syllabus for BIOSTAT646