STATS 545 - High Throughput Molecular Genomic and Epigenomic Data Analysis
Section: 001
Term: WN 2018
Subject: Statistics (STATS)
Department: LSA Statistics
Credits:
3
Requirements & Distribution:
BS
Waitlist Capacity:
10
Consent:
With permission of instructor.
Advisory Prerequisites:
STATS 400 (or equivalent) and graduate standing: or permission of instructor. Students should have completed at least programming class with a passing grade. Preparation in biiology or quantitative analysis also recommended.
BS:
This course counts toward the 60 credits of math/science required for a Bachelor of Science degree.
Repeatability:
May not be repeated for credit.
Primary Instructor:
Instructor:
Instructor:

This course will cover statistical methods used to analyze data in experimental molecular biology, with an emphasis on gene and protein expression array data. Topics: data acquisition, databases, low level processing, normalization, quality control, statistical inference (group comparisons, cyclicity, survival), multiple comparisons, statistical learning algorithms, clustering visualization, and case studies.

STATS 545 - High Throughput Molecular Genomic and Epigenomic Data Analysis
Schedule Listing
001 (LEC)
P
21255
Open
20
 
-
TuF 11:30AM - 1:00PM
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