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[[File:Lp54-gain-loss.png|200px|thumbnail|Figure 1. Gains & losses of host-defense genes among Lyme pathogen genomes (Qiu & Martin 2014)]]
[[File:Lp54-gain-loss.png|200px|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 profound 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.  


Genome information is revolutionizing virtually all aspects of life sciences including basic basic, 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.  
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 includes college-level courses in molecular biology, cell biology, and genetics. Introductory courses in computer programming and statistics are preferred but not strictly required.
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==

Revision as of 16:02, 22 June 2019

Biomedical Genomics
July 8-19, 2019
Instructor: Weigang Qiu, Ph.D.
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
Office: B402 Belfer Research Building, 413 East 69th Street, New York, NY 10021, USA
Email: weigang@genectr.hunter.cuny.edu
Lab Website: http://diverge.hunter.cuny.edu/labwiki/

Figure 1. Gains & losses of host-defense genes among Lyme pathogen genomes (Qiu & Martin 2014)

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, and single-cell genomics
  • Visualize and explore genomics data using RStudio
  • Replicate key results using a data set associated with a primary research paper

Useful 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: 4 x 25 pts = 100 pts
  • Final report: 50 pts

Total: 200 pts

Course Schedule

  • July 8 (Mon), 8:40-12:10
  • July 9 (Tu), 8:40-12:10
  • July 10 (Wed), 8:40-12:10
  • July 11 (Thur), 8:40-12:10
  • July 12 (Fri), 8:40-12:10
  • July 15 (Mon), 8:00-12:10
  • July 16 (Tu), 8:00-12:10
  • July 17 (Wed), 8:00-12:10
  • July 18 (Thur), 8:00-12:10
  • July 19 (Fri), 8:00-12:10

Papers & Data

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