Class Central is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Harvard University

Data Analysis for Genomics

Harvard University via edX Professional Certificate


Advances in genomics have triggered fundamental changes in medicine and research. Genomic datasets are driving the next generation of discovery and treatment, and this series will enable you 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. These courses are perfect for those who seek advanced training in high-throughput technology data. Problem sets will require coding in the R language to ensure mastery of key concepts. In the final course, you’ll investigate data analysis for several experimental protocols in genomics.

Enroll now to unlock the wealth of opportunities in modern genomics.


Courses under this program:
Course 1: Introduction to Bioconductor

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

Course 2: Case Studies in Functional Genomics

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

Course 3: Advanced Bioconductor

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


Taught by

Constance Chen, Peter Kraft, Shannan Ho Sui, Radhika Khetani, Vincent Carey, Oliver Hofmann, Meeta Mistry, X. Shirley Liu, Rafael Irizarry and Michael Love


Start your review of Data Analysis for Genomics

Never Stop Learning.

Get personalized course recommendations, track subjects and courses with reminders, and more.