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CANC 604 Cancer Genomics Data Analyses (1 credit)

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Offered by: Goodman Cancer Institute (Faculty of Medicine and Health Sciences)

Administered by: Graduate Studies

Overview

CANC : An introduction to the basic principles underlying genome-wide analysis of high-dimensional genomic data such as gene expression, epigenetic, or proteomic or data through the lens of RNA-seq expression data to illustrate concepts such as assessing data quality, the need for normalization, the impact of filtering, and testing for differential expression.

Terms: This course is not scheduled for the 2023-2024 academic year.

Instructors: There are no professors associated with this course for the 2023-2024 academic year.

  • Prerequisites: BIOL 200, BIOC 212, ANAT 212 or permission of the instructor.

  • 1. An understanding of transcription, translation, and how RNA-seq data measure transcription is required.

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