Statistics (STAT) Courses>Statistical Methods for Genomic Data

STAT465 - Statistical Methods for Genomic Data

Description

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.

Units

1.5

Hours: lecture-lab-tutorial

3-0-0

Note(s)

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

Prerequisites

  • Complete all of:
    • STAT350 - Mathematical Statistics I (1.5)
    • STAT353 - Applied Regression Analysis (1.5)
  • or permission of the department.

Course offered by

Department of Mathematics and Statistics

Course schedules

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

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