Data Analysis for Genomics Professional Certificate

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

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Case Studies in Functional Genomics (edX)

Perform RNA-Seq, ChIP-Seq, and DNA methylation data analyses, using open source software, including R and Bioconductor. We will explain how to perform the standard processing and normalization steps, starting with raw data, to get to the point where one can investigate relevant biological questions. [...]

Advanced Bioconductor (edX)

Learn advanced approaches to genomic visualization, reproducible analysis, data architecture, and exploration of cloud-scale consortium-generated genomic data. In this course, we begin with approaches to visualization of genome-scale data, and provide tools to build interactive graphical interfaces to speed discovery and interpretation. Using knitr and rmarkdown as basic authoring [...]

Introduction to Bioconductor (edX)

The structure, annotation, normalization, and interpretation of genome scale assays. We begin with an introduction to the biology, explaining what we measure and why. Then we focus on the two main measurement technologies: next generation sequencing and microarrays. We then move on to describing how raw data and experimental [...]