CSE 5243 is offe#9B0808 under the auspices of the
Department of Computer Science and Engineering, The Ohio State University. It
is an elective course and will serve all those interested and enthusiastic
about bioinformatics and data visualization.
Course Description
With the fast
development of high throughput technologies such as microarray and next
generation sequencing (NGS), bioinformatics becomes an essential part of
biomedical research on human diseases. Analysis of the large amount of high
throughput data becomes the new bottleneck in many research projects. The goal
of this course is to let students get familiar with the commonly used
bioinformatics data analysis tools via hands-on training and discussion on both
classical and state-of-the-art literature. The topics include analysis and
visualization of both microarray and NGS data for genotyping, and epigenomics,
and transcriptome studies in human diseases as well as advanced methods based
on gene network inference and analysis.
Course Contents: R, Bioconductor, Microarrays, RNA-sequence
data, bioinformatics, genotyping, epigenomics, transcriptome, visualization,
co-expression network
The Highlights: R, Bioconductor, machine learning, visualization,
transcriptomics, micorarrays, RNA-seq
Text Books and
Instructors
Grading Assistant: Instructors
Time: TR 1:00-1:55 PM; Lincoln Tower 240
Office Hours
Kun Huang: By Appointment. Contact at kun.huang dot osumc dot eduRaghu Machiraju: DL779: M 2:00-3:00 PM, W:3:00-4:00PM; LT Third Floor T, R: 2:00-3:00 PM (after class). Contact at machiraju dot 1 at osu dot edu.
Grade Distribution: Assignments: 40%, Quizzes:20%, Final Project: 40%
Class Help/Watering Hole: Piazza - https://piazza.com/osu/autumn2015/bmi7830-cse5559/home
Chapters below allude to text by Sorin Drahici !
Week 1 |
8/25: Overview of high throughput technologies, online resources, and public data repositories (pdf) |
8/27: 8/27 Review of biology / basic bioinformatics techniques (pdf) |
Chapter 2 from text; Biology Primer(Lander): https://www.youtube.com/watch?v=TnpCMgtDPgk |
Week 2 |
9/1: - Use of high throughput gene expression data in biomedical research (pdf) |
9/3: Laboratory techniques for measuring gene expression- Prof. Jeff Parvin, Biomedical Informatics (pdf) |
Chapter 3, Papers discussed in slide decks. |
Week 3 |
9/8: Introduction to R and Bioconductor I (pdf) |
9/10:
R and Bioconductor II (pdf) |
Computing
Basics for Bioinformatics - Self-paced Learning, Chapters 3,4/6,7, |
Week 4 |
9/15: Normalization of microarray data (pdf) |
9/17: Genetics and Translational Research - Prof. Chris Bartlett, Nationwide Children (pdf) |
Chapter 20 |
Week 5 |
9/22: Normalization (pdf) |
9/24: Comparative Analysis: HT - (pdf) |
Chapter 11, Chapter 12, Chapter 16, Chapter 20 |
Week 6 |
9/29: Comparative Analysis - multiple test comparison (pdf) |
10/1: Unsupervised learning in bioinformatics (pdf) |
Chapter 16, Chapter 20, Chapter 18 |
Week 7 |
10/6: Supervised learning in bioinformatics (pdf) |
10/8:
Visualization (pdf
- Original), |
Chapter 18, Chapter 29, Chaper 17 |
Week 8 |
10/13:
Gene network analysis |
10/15: Holiday |
Lab2 Announced on 10/13. |
Week 9 |
10/20: Gene Ontology and Pathway Analysis (pdf) - Guest Lecture, Dr. Jianying Zhang, OSUMC |
10/22: Small Sample Size Analyis (pdf) - LIMMA, Sample Size Estimation - Linbao Yu |
Lab2 Due - 10/22 |
Week 10 |
10/27: Data Foreniscs - Prof. Kevin Coombes |
10/29: Introduction to NGS (pdf)- Gulcin Ozer |
Project Proposal Due - 10/29. |
Week 11 |
11/3: Sequence alignment of NGS (pdf) - Selen Yilmaz, Gulcin Ozer |
11/5: Sequence alignment for RNA-seq data (pdf) |
Lab3 announced on 11/3. |
Week 12 |
11/10: Sequence alignment for RNA-seq data (pdf) |
11/19: Comparative analysis of RNA-seq data (pdf) |
Lab3 due on 11/13. |
Week 13 |
11/17: Review/De novo analysis of RNA-seq data (pdf) |
11/19: Project Presentations |
Dwell
on projects. |
Week 14 |
11/24: TCGA (pdf), Quiz 3 |
11/26 Thanksgiving Holiday - have a good one. |
Quiz
3 on 11/24. |
Week 15 |
12/1: Networking and Visualization (pdf) |
12/3: Networking and Visualization (pdf) |
Lab 4 Due on 12/5 |
Week 16 |
12/8: Networking and Visualization (pdf), Quiz 4 |
--- DONE --- |
Quiz 4 on 12/8 |
The Final Presentation: Friday Dec 11 2:00pm-4:00 pm
Quizz: 9/10, 10/20, 11/19, 12/4
Final Project Proposal - Integrative Fishing in TCGA waters
Due: October
29, 2015
Do the following:
Labs
Useful
Links
Papers:
Russ Altman: His review
of papers at AMIA TBI conferences can help you select projects.
The venerable p-value - It is ubiquitously used by the bioinformatics
community to determine the viability of their hypotheses results. However, it
is running into a maelstrom of criticism as noted in the following commentaries
found in the first two links. The other two in the list below are more informed
manuscripts that dwell on this controversy.
http://debunkingdenialism.com/2015/04/01/new-nature-methods-paper-argues-that-p-values-should-be-discarded/
http://www.nature.com/news/statistics-p-values-are-just-the-tip-of-the-iceberg-1.17412
http://www.nature.com/news/scientific-method-statistical-errors-1.14700
http://www.nature.com/nmeth/journal/v12/n3/full/nmeth.3288.html
Data:
Websites:
Lior Pachter Blog: Do
read his musings
on Network Nonsense
Russ Altman: His review
of papers at AMIA TBI conferences can help you select projects
Tutorials:
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