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INFO-B 636 Genomic Data Analytics and Precision Medicine

3 credits

  • Prerequisites: None
  • Delivery: On-Campus
  • This advanced course covers how massive clinical and biomedical genomic sequencing datasets from various sequencing platforms motivate computational needs and tasks for analysis, how to devise approaches for analyzing these datasets, how to develop sound hypotheses and predictions from them, and related ethical, privacy, and legal issues.

    Learning Outcomes

    1. Analyze genomic data appropriately considering the sequencing technique and molecular biology.
    2. Perform sequence alignment and genome assembling.
    3. Align and quantitate a) DNA sequence reads of various platforms, b) RNA sequence reads of various platforms, c) Microbial DNA and RNA sequence reads, and d) ChIP-seq and CLIP-seq reads.
    4. Analyze microbial genomics, metagenomics, metatranscriptomics, operons and transcription units taxonomic mapping, microbial abundance, interactions, and pathways.
    5. Compare and contrast computational methods for performing peak calling and benchmarking and for analyzing ChIP-seq, CLIP-seq, and post-transcriptional regulation.
    6. Analyze diverse datasets, including small RNA sequencing, polyA sequencing, and protein occupancy profiling.
    7. Evaluate genetic and somatic variation, differences among variant calling approaches, expression quantitative trait loci identification, and related issues and considerations.
    8. Evaluate personalized sequencing projects with respect to ethical considerations.
    9. Write a report and give an oral presentation grounded in an appropriate review of the literature.