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
OnlinePerform RNA-Seq, ChIP-Seq, and DNA methylation data analyses, using open source software, including R and Bioconductor.Free*5 weeks longClosed- OnlineLearn advanced approaches to genomic visualization, reproducible analysis, data architecture, and exploration of cloud-scale...Free*5 weeks longClosed
- OnlineThe structure, annotation, normalization, and interpretation of genome scale assays.Free*5 weeks longClosed
