Southwest-University: Difference between revisions
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<center>'''Lab Website:''' http://diverge.hunter.cuny.edu/labwiki/</center> | <center>'''Lab Website:''' http://diverge.hunter.cuny.edu/labwiki/</center> | ||
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[[File:Lp54-gain-loss.png| | [[File:Lp54-gain-loss.png|400px|thumbnail|Figure 1. Gains & losses of host-defense genes among Lyme pathogen genomes (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 | 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 | 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. | 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 | 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== | ==Learning goals== | ||
By the end of this course successful students will be able to: | By the end of this course successful students will be able to: | ||
* Describe next-generation sequencing (NGS) technologies & contrast it with traditional Sanger sequencing | * 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 | * 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 | * Visualize and explore genomics data using RStudio | ||
* Replicate key results using a data set | * Replicate key results using a raw data set produced by a primary research paper | ||
== | ==Web Links== | ||
* Install R and R Studio | * Install R and R Studio | ||
* Unix Tutorial | * Unix Tutorial | ||
Line 32: | Line 32: | ||
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 | ||
* Quizzes: | * Quizzes: 2 x 25 pts = 50 pts | ||
* Final | * Mid-term: 50 pts | ||
* Final presentation: 50 pts | |||
Total: 200 pts | Total: 200 pts | ||
==Course Schedule== | ==Course Schedule== | ||
{| class="wikitable" | |||
|- | |||
! Date & Hour !! Tutorials !! Paper !! Quiz & Exam | |||
|- | |||
| July 8 (Mon), 8:40-12:10 || Introduction; R Tutorial I; NGS || NGS || | |||
|- | |||
| July 9 (Tu), 8:40-12:10 || NGS; R Tutorial II || NGS || | |||
|- | |||
| July 10 (Wed), 8:40-12:10 || Microbiome I; R Tutorial III || Fish diet || Quiz I | |||
|- | |||
| July 11 (Thur), 8:40-12:10 || Microbiome II; R Tutorial IV || Lyme pathogen || | |||
|- | |||
| July 12 (Fri), 8:40-12:10 || || || Mid-term Exam | |||
|- | |||
| Weekend || Break | |||
|- | |||
| July 15 (Mon), 8:00-12:10 || Transcriptome || essential human genes || | |||
|- | |||
| July 16 (Tu), 8:00-12:10 || Proteome || breast cancer || | |||
|- | |||
| July 17 (Wed), 8:00-12:10 || Genomics I || TB || Quiz II | |||
|- | |||
| July 18 (Thur), 8:00-12:10 || Genomics II || Human genome variations || | |||
|- | |||
| July 19 (Fri), 8:00-12:10|| Presentations | |||
|} | |||
==Papers & | ==Papers & Datasets== | ||
{| class="wikitable sortable" | {| class="wikitable sortable" | ||
|- | |- | ||
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| Transcriptome & Regulome || [https://bmcmedgenomics.biomedcentral.com/articles/10.1186/s12920-019-0477-8 Nava_etal_2019_BMCGenomics] || Tables S2 & S3 || RNA-Seq & CHIP-Seq | | Transcriptome & Regulome || [https://bmcmedgenomics.biomedcentral.com/articles/10.1186/s12920-019-0477-8 Nava_etal_2019_BMCGenomics] || Tables S2 & S3 || RNA-Seq & CHIP-Seq | ||
|- | |- | ||
| | | Proteome || [https://www.ncbi.nlm.nih.gov/pubmed/28232952 Qiu_etal_2017_NPJ] || (to be posted) || SILAC | ||
|- | |- | ||
| | | Population genomics (Lyme) || [https://jcm.asm.org/content/56/11/e00940-18.long Di_etal_2018_JCM] || [https://github.com/weigangq/ocseq Data & R codes] || Amplicon sequencing (antigen locus) | ||
|- | |- | ||
| | | Population genomics/GWAS (Human) || [https://science.sciencemag.org/content/351/6274/737.long Simonti_etal_2016_Science] || [https://science.sciencemag.org/highwire/filestream/673591/field_highwire_adjunct_files/1/aad2149-Simonti-SM.Table.S2.xlsx Table S2] || whole-genome sequencing (WGS); [http://www.internationalgenome.org/ 1000 Genome Project (IGSR)] | ||
|- | |- | ||
| | | TB surveillance || [https://jcm.asm.org/content/53/7/2230 Brow_etal_2015] || [https://www.ebi.ac.uk/ena/data/view/PRJEB9206 Sequence Archives]|| Whole-genome sequencing (WGS) | ||
|- | |- | ||
| Example || Example || Example || Example | | Example || Example || Example || Example |
Revision as of 02:17, 23 June 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
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 and R Studio
- Unix Tutorial
- Textbook
Quizzes and Exams
Student performance will be evaluated by attendance, three (4) quizzes and a final report:
- Attendance: 50 pts
- Quizzes: 2 x 25 pts = 50 pts
- Mid-term: 50 pts
- Final presentation: 50 pts
Total: 200 pts
Course Schedule
Date & Hour | Tutorials | Paper | Quiz & Exam |
---|---|---|---|
July 8 (Mon), 8:40-12:10 | Introduction; R Tutorial I; NGS | NGS | |
July 9 (Tu), 8:40-12:10 | NGS; R Tutorial II | NGS | |
July 10 (Wed), 8:40-12:10 | Microbiome I; R Tutorial III | Fish diet | Quiz I |
July 11 (Thur), 8:40-12:10 | Microbiome II; R Tutorial IV | Lyme pathogen | |
July 12 (Fri), 8:40-12:10 | Mid-term Exam | ||
Weekend | Break | ||
July 15 (Mon), 8:00-12:10 | Transcriptome | essential human genes | |
July 16 (Tu), 8:00-12:10 | Proteome | breast cancer | |
July 17 (Wed), 8:00-12:10 | Genomics I | TB | Quiz II |
July 18 (Thur), 8:00-12:10 | Genomics II | Human genome variations | |
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 |