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

Online

Perform RNA-Seq, ChIP-Seq, and DNA methylation data analyses, using open source software, including R and Bioconductor.

Price
Free*
Duration
5 weeks long
Registration Deadline
Available now
Online

The structure, annotation, normalization, and interpretation of genome scale assays.

Price
Free*
Duration
4 weeks long
Registration Deadline
Available now
Online

Learn advanced approaches to genomic visualization, reproducible analysis, data architecture, and exploration of cloud-scale consortium-generated genomic data.

Price
Free*
Duration
5 weeks long
Registration Deadline
Available now

Instructors

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