Data Analysis for Genomics by Harvard
Skills Covered: Bioconductor, Functional Genomics, Advanced Bioconductor, Next Generation Sequencing, Microarrays, Preprocessing and Normalization, Bioconductor Genomic Ranges Utilities, Genomic Annotation, Genome Scale Assays, Analyzing RNA-seq data, Analyzing DNA methylation data, Analyzing ChIP Seq data, Genomic Data, Visualization of Genomic Data, Targeted Interrogation, Cloud-Scale Genomic Archives
ABOUT THIS PROFESSIONAL CERTIFICATION
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.
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.
- Companies are leveraging the power of data analysis to drive innovation. Google data analysts use R to track trends in ad pricing and illuminate patterns in search data. Pfizer created customized packages for R so scientists can manipulate their own data.
- Data Scientists are few in number and high in demand. (source: TechRepublic)
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