STAT 465

Statistical Methods for Genomic Data

Units: 1.5

Hours: 3-0-0

Introduction to genomic data and statistical methodology for its analysis; examples of data may include single-nucleotide polymorphisms or gene expression levels, generated from microarrays or next-generation sequencing. Statistical techniques may include data preprocessing, filtering, normalization, exploratory methods, visualization, dimension reduction, differential expression, generalized linear models, corrections for multiple comparisons, clustering, gene ontology analyses, genome-wide association studies.

Note:

  • May be offered as a joint undergraduate and graduate class.

Prerequisites:

Undergraduate course in Statistics offered by the Department of Mathematics and Statistics in the Faculty of Science.

Schedules:
Summer 2019 Fall 2019 Spring 2020

Summer timetable available: February 15. Fall and Spring timetables available: May 15.

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