Southwest-University: Difference between revisions
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<center>'''Biomedical Genomics'''</center> | <center>'''Biomedical Genomics'''</center> | ||
<center>July 8-19, 2019</center> | <center>July 8-19, 2019</center> | ||
<center>'''Instructor:''' Weigang Qiu, Ph.D.<br>Professor, Department of Biological Sciences, City University of New York, Hunter College & Graduate Center<br>Adjunct Faculty, Department of Physiology and Biophysics | <center>'''Instructor:''' Weigang Qiu, Ph.D.<br>Professor, Department of Biological Sciences, City University of New York, Hunter College & Graduate Center<br>Adjunct Faculty, Department of Physiology and Biophysics, | ||
Institute for Computational Biomedicine, Weil Cornell Medical College</center> | Institute for Computational Biomedicine, Weil Cornell Medical College</center> | ||
<center>'''Office:''' B402 Belfer Research Building, 413 East 69th Street, New York, NY 10021, USA</center> | <center>'''Office:''' B402 Belfer Research Building, 413 East 69th Street, New York, NY 10021, USA</center> | ||
<center>'''Email:''' weigang@genectr.hunter.cuny.edu</center> | <center>'''Email:''' weigang@genectr.hunter.cuny.edu</center> | ||
<center>'''Lab Website:''' http://diverge.hunter.cuny.edu/labwiki/</center> | <center>'''Lab Website:''' http://diverge.hunter.cuny.edu/labwiki/</center> | ||
<br> | |||
<center>'''Host''': Shunqin Zhu (祝顺琴), Ph.D.<br>Associate Professor, School of Life Science, South West University</center> | |||
---- | ---- | ||
[[File:Lp54-gain-loss.png| | [[File:Lp54-gain-loss.png|300px|thumbnail|Figure 1. Gains & losses of host-defense genes among Lyme pathogen genomes ([https://www.ncbi.nlm.nih.gov/pubmed/24704760 Qiu & Martin 2014])]] | ||
==Course Overview== | ==Course Overview== | ||
Welcome to BioMedical Genomics, a computer workshop for advanced undergraduates and graduate students. A genome is the total genetic content of an organism. Driven by breakthroughs such as the decoding of the first human genome and next-generation DNA -sequencing technologies, biomedical sciences are undergoing a rapid and irreversible transformation into a highly data-intensive field. | Welcome to BioMedical Genomics, a computer workshop for advanced undergraduates and graduate students. A genome is the total genetic content of an organism. Driven by breakthroughs such as the decoding of the first human genome and next-generation DNA -sequencing technologies, biomedical sciences are undergoing a rapid and irreversible transformation into a highly data-intensive field. | ||
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==Web Links== | ==Web Links== | ||
* Install R | * Install R base: https://cloud.r-project.org | ||
* | * Install R Studio (Desktop version): http://www.rstudio.com/download | ||
* | * Download: [http://www.r4all.org/books/datasets R datasets] | ||
* A reference book: [https://r4ds.had.co.nz/ R for Data Science (Wickharm & Grolemund)] | |||
==Quizzes and Exams== | ==Quizzes and Exams== | ||
Student performance will be evaluated by attendance, three (4) quizzes and a final report: | Student performance will be evaluated by attendance, three (4) quizzes and a final report: | ||
* Attendance: 50 pts | * Attendance: 50 pts | ||
* Assignments: 5 x 10 = 50 pts | |||
* Quizzes: 2 x 25 pts = 50 pts | * Quizzes: 2 x 25 pts = 50 pts | ||
* Mid-term: 50 pts | * Mid-term: 50 pts | ||
* Final presentation: 50 pts | * Final presentation: 50 pts | ||
Total: | Total: 250 pts | ||
==Course Schedule== | ==Course Schedule== | ||
{| class="wikitable" | {| class="wikitable" | ||
|- | |- | ||
! Date & Hour !! | ! Date & Hour !! Tutorials !! Assignment !! Quiz & Exam | ||
|- | |- | ||
| July 8 (Mon), 8:40-12:10 || Introduction; R Tutorial I; NGS || NGS || | | July 8 (Mon), 8:40-12:10 || Introduction; R Tutorial I; | ||
[[File:R-part-1-small.pdf|thumbnail|Lecture slides]] | |||
|| | |||
Assignment #1 (create a WORD document including scripts & graphs) | |||
* Install R/R studio and the "tidyverse" package on your own computer | |||
* Recreate Script 1 & Mini-Practical | |||
* Show help page for function "seq" | |||
* Download dataset | |||
** Create a new folder (e.g., Desktop/rtutor) | |||
** Create a sub-folder (e.g., Desktop/rtutor/data/) | |||
** Download from http://www.r4all.org/the-book/datasets | |||
** Save to the sub-folder | |||
** Unzip the file | |||
|| | |||
|- | |||
| July 9 (Tu), 8:40-12:10 || NGS; R Tutorial II || | |||
Assignment #2 | |||
* List pros & cons of Sanger vs NGS | |||
* Compare accuracy, read length, and error rate between Illumina and PacBio | |||
* Describe sequence information captured with each of the following file formats: FASTA, FASTQ, SAM, VCF | |||
* Wide vs Tall data frames | |||
* Variable names (informative, case sensitive) | |||
* Read file | |||
|| | |||
|- | |- | ||
| July | | July 10 (Wed), 8:40-12:10 || Microbiome I; R Tutorial III || | ||
Assignment #3 | |||
|| Quiz I | |||
|- | |- | ||
| July | | July 11 (Thur), 8:40-12:10 || Microbiome II; R Tutorial IV || | ||
Assignment #4 | |||
|| | |||
|- | |- | ||
| July | | July 12 (Fri), 8:40-12:10 || || || Mid-term Exam | ||
|- | |- | ||
| | | Weekend || Break | ||
|- | |- | ||
| July 15 (Mon), 8:00-12:10 || | | July 15 (Mon), 8:00-12:10 || Transcriptome; R Tutorial V || | ||
Assignment #5 | |||
|| | |||
|- | |- | ||
| July 16 (Tu), 8:00-12:10 || | | July 16 (Tu), 8:00-12:10 || Proteome || | ||
|| | |||
|- | |- | ||
| July 17 (Wed), 8:00-12:10 || | | July 17 (Wed), 8:00-12:10 || Genomics I || | ||
|| Quiz II | |||
|- | |- | ||
| July 18 (Thur), 8:00-12:10 || | | July 18 (Thur), 8:00-12:10 || Genomics II || || | ||
|- | |- | ||
| July 19 (Fri), 8:00-12:10 | | July 19 (Fri), 8:00-12:10|| Presentations | ||
|} | |} | ||
Revision as of 06:05, 8 July 2019
Professor, Department of Biological Sciences, City University of New York, Hunter College & Graduate Center
Adjunct Faculty, Department of Physiology and Biophysics, Institute for Computational Biomedicine, Weil Cornell Medical College
Associate Professor, School of Life Science, South West University
Course Overview
Welcome to BioMedical Genomics, a computer workshop for advanced undergraduates and graduate students. A genome is the total genetic content of an organism. Driven by breakthroughs such as the decoding of the first human genome and next-generation DNA -sequencing technologies, biomedical sciences are undergoing a rapid and irreversible transformation into a highly data-intensive field.
Genome information is revolutionizing virtually all aspects of life sciences including basic research, medicine, and agriculture. Meanwhile, use of genomic data requires life scientists to be familiar with concepts and skills in biology, computer science, as well as data analysis.
This workshop is designed to introduce computational analysis of genomic data through hands-on computational exercises, using published studies.
The pre-requisites of the course are college-level courses in molecular biology, cell biology, and genetics. Introductory courses in computer programming and statistics are preferred but not strictly required.
Learning goals
By the end of this course successful students will be able to:
- Describe next-generation sequencing (NGS) technologies & contrast it with traditional Sanger sequencing
- Explain applications of NGS technology including pathogen genomics, cancer genomics, human genomic variation, transcriptomics, meta-genomics, epi-genomics, and microbiome.
- Visualize and explore genomics data using RStudio
- Replicate key results using a raw data set produced by a primary research paper
Web Links
- Install R base: https://cloud.r-project.org
- Install R Studio (Desktop version): http://www.rstudio.com/download
- Download: R datasets
- A reference book: R for Data Science (Wickharm & Grolemund)
Quizzes and Exams
Student performance will be evaluated by attendance, three (4) quizzes and a final report:
- Attendance: 50 pts
- Assignments: 5 x 10 = 50 pts
- Quizzes: 2 x 25 pts = 50 pts
- Mid-term: 50 pts
- Final presentation: 50 pts
Total: 250 pts
Course Schedule
Date & Hour | Tutorials | Assignment | Quiz & Exam |
---|---|---|---|
July 8 (Mon), 8:40-12:10 | Introduction; R Tutorial I; |
Assignment #1 (create a WORD document including scripts & graphs)
|
|
July 9 (Tu), 8:40-12:10 | NGS; R Tutorial II |
Assignment #2
|
|
July 10 (Wed), 8:40-12:10 | Microbiome I; R Tutorial III |
Assignment #3 |
Quiz I |
July 11 (Thur), 8:40-12:10 | Microbiome II; R Tutorial IV |
Assignment #4 |
|
July 12 (Fri), 8:40-12:10 | Mid-term Exam | ||
Weekend | Break | ||
July 15 (Mon), 8:00-12:10 | Transcriptome; R Tutorial V |
Assignment #5 |
|
July 16 (Tu), 8:00-12:10 | Proteome | ||
July 17 (Wed), 8:00-12:10 | Genomics I | Quiz II | |
July 18 (Thur), 8:00-12:10 | Genomics II | ||
July 19 (Fri), 8:00-12:10 | Presentations |
Papers & Datasets
Omics Application | Paper link | Data set | NGS Technology |
---|---|---|---|
Microbiome | Rimoldi_etal_2018_PlosOne | S1 Dataset | 16S rDNA amplicon sequencing |
Transcriptome | Wang_etal_2015_Science | Tables S2 & S4 | RNA-Seq |
Transcriptome & Regulome | Nava_etal_2019_BMCGenomics | Tables S2 & S3 | RNA-Seq & CHIP-Seq |
Proteome | Qiu_etal_2017_NPJ | (to be posted) | SILAC |
Population genomics (Lyme) | Di_etal_2018_JCM | Data & R codes | Amplicon sequencing (antigen locus) |
Population genomics/GWAS (Human) | Simonti_etal_2016_Science | Table S2 | whole-genome sequencing (WGS); 1000 Genome Project (IGSR) |
TB surveillance | Brow_etal_2015 | Sequence Archives | Whole-genome sequencing (WGS) |
Example | Example | Example | Example |
Example | Example | Example | Example |
Example | Example | Example | Example |