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Department of Statistics

Stat 588

 588—Genomic Data Science [=BIOL 588]. (3) (Prereq: STAT201, STAT205 or STAT 515 or STAT 509 or equivalent, must earn a grade C or betterThis course focuses on quantitative knowledge for interdisciplinary applications in genetics as well as “hands-on” experience in analyzing genetic data. In this course, students will have programming exercises in using analysis tools to conduct genome-wide analysis, annotation and interpretation of genetic data. The lab sections of this course will focus on using R/Bioconductor software packages as tools for analyses.

Course Homepage: Recent course

Usually Offered: Spring Semester

Learning Objectives:

  1. Demonstrate basic knowledge of statistical tools applied to human genetics
  2. Demonstrate basic R/Bioconductor programming skills
  3. Interpret results and perform simple model diagnoses
  4. Analyze appropriate literature to develop a literature review based on a selectedtopic (graduate students).

Current Textbook:  

  1. Gondo (2015): Primer to Analysis of Genomic Data Using R. Springer. ISBN 978-3-319-14475-7
  2. Hahne, Huber, Gentleman, and Falcon (2008): Bioconductor Case Studies
Topics Week      
Introduction to Biology and R Week 1
Review Statistics I-II/Lab (data import/export, simple data manipulation, missing values, writing functions). Weeks 2-3
Simple marker association test /Lab (simple genomic data analysis using R) Weeks 4-5 
Genome-wide association study Weeks 6-7 
Population structure, supervised learning with high dimensional data and categorical predictors Week 8
Introduction to gene expression microarray Week 9
Gene expression analysis (microarray, RNAseq) Weeks 10-12
Database and functional annotation Week 13
Machine learning to gene expression data /working with high performance computing clusters Week 14
Selected topics Week 15

The above textbook and course outline should correspond to the most recent offering of the course by the Statistics Department. Please check the current course homepage or with the instructor for the course regulations, expectations, and operating procedures.  

Contact Faculty: Yen-Yi Ho

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