Data Analysis for Genomics

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Data Analysis for Genomics provided by edX is a comprehensive online course, which lasts for 13 weeks long, 2-4 hours a week. Data Analysis for Genomics is 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. Upon completion of the course, you can receive an e-certificate from edX. The course is taught in Englishand is $447.00. Visit the course page at edX for detailed price information.

Overview
  • 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.

Syllabus
  • 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.