What you'll learn

  • Advanced techniques to analyze genomic data
  • How to structure, annotate, normalize, and interpret genome-scale assays
  • How to bridge diverse genomic assay and annotation structures to data analysis and research presentations via innovative approaches to computing
  • How to analyze data from several experimental protocols, using open source software, including R and Bioconductor

About this series

The Genomics Data Analysis XSeries is an advanced series that will enable students to analyze and interpret data generated by modern genomics technology.

Using open-source software, including R and Bioconductor, you will acquire skills to analyze and interpret genomic data.

This XSeries is perfect for those who seek advanced training in high-throughput technology data. Problem sets will require coding in the R language to ensure learners fully grasp and master key concepts. The final course investigates data analysis for several experimental protocols in genomics.

This series includes

Instructors

  • Professor of Biostatistics, T.H. Chan School of Public Health
  • Assistant Professor, Departments of Biostatistics and Genetics, UNC Gillings School of Global Public Health
  • Professor of Medicine (Biostatistics) in the Channing Division of Network Medicine, Brigham and Women’s Hospital, Harvard Medical School

Associated Schools

  • Harvard T.H. Chan School of Public Health