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Biostatistics

BSMS 222, Fall

Time: Monday (5) and Wednesday (5)

Location: Offline and Online simultaneously (대면+비대면 실시간 강의)

Lecturer

Joon-Yong An, PhD

Assistant Professor of Human Genetics

School of Biosystem and Biomedical Science, College of Health Science

1. General Course Information

1.1. Course Details

Coordinating Unit: School of Biosystem and Biomedical Science, College of Health Science Level: Undergraduate

1.2. Course Introduction

Statistics is fundamental in modern biology because it is integral in the design, analysis, and interpretation of experiments. The main aim of the course is to develop data science and hands-on programming skills in high-throughput biological research. The course will introduce concepts and hand-on skills that can help you tackle real-world data analysis challenges.

This class contains hands-on coding exercise in every lecture, so please bring your laptop for the class (노트북 필수)

2. Aims, Objectives & Graduate Attributes

2.1 Course Aims

The aim of this course is to familiarize students with the discipline of biostatistics and basic analytic skills. Students will develop an appreciation of modern application in biostatistics while gaining a detailed understanding of the analytic fundamentals from data modality to programming language. Over the semester, students will be placed into hardcore training in programming exercise. We are learning R and UNIX for statistical computing and graphics.

2.2 Learning Objectives

After successfully completing this course you should be able to:

  1. Understand the basic programming for statistical analysis in genomic data

  2. Understand the basic concepts for modern genomic research

  3. Become confident in using R for genomics analyses

  4. Gain hand-on experience in data visualization and wrangling

3. Learning Resources

by Rafael A. Irizarry, 2019. https://rafalab.github.io/dsbook/

Computational Genomics with R by Altuna Akalin, 2020 https://compgenomr.github.io/book/

Bioinformatics Workshop Gitbook by Juan C. Santos & Randy Ortiz, 2022 https://corytophanes.github.io/BIO_BIT_Bioinformatics_209/getting-started-with-r.html

4. Teaching & Learning Activities

4.1 Learning Activities

Session 1 R

Introduction to biostatistics (week 1-1)

Introduction to Rstudio (week 1-1)

R basics (week 1-2)

Programming basics (week 2-1)

Tidyverse (week 3-2 & 5-1)

Session 2 Data viz

ggplot

Distribution

Data visualization in practice

Robust summaries

Session 3. Data modality and experimental design

RNA sequencing: Case Study

Multi Omics: Case Study

UNIX

김준 교수님 튜토리얼

유닉스 튜토리얼

5. Misc.

Biological Data Science Materials

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