Computational Genomics Summer 2026: Difference between revisions
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2-5pm, July 13 - Aug 13, 2026
Course link on gitee
Guest Instructor: Weigang Qiu, Ph.D.
Professor, Department of Biological Sciences, City University of New York, Hunter College & Graduate Center
Adjunct Faculty, Department of Systems and Computational Biomedicine, Weil Cornell Medical College
Office: B402 Belfer Research Building, 413 East 69th Street, New York, NY 10021, USA
Email: wqiu@hunter.cuny.edu
Lab Website: https://wiki.genometracker.org
Host & Assistants
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[[File:Banner-comp-genomics.png|800px|center]] | [[File:Banner-comp-genomics.png|800px|center]] | ||
<center>2-5pm, July 13 - Aug 13, 2026</center> | <center>2-5pm, July 13 - Aug 13, 2026</center> | ||
<center>[https://edu.gitee.com/huntercollege/courses/5124/noticeboard Course link on gitee]</center> | |||
<center>'''Guest 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 Systems and Computational Biomedicine, Weil Cornell Medical College</center> | <center>'''Guest 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 Systems and 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> | ||
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By the end of this course successful students will be able to: | By the end of this course successful students will be able to: | ||
* ('''Tree-thinking''' skills) Compare and analyze genomes in a phylogenetic framework | * ('''Tree-thinking''' skills) Compare and analyze genomes in a phylogenetic framework | ||
* ('''Algorithm-thinking''' skills) Implement the evolutionary algorithms in a programming language of choice (R, Python, or others) | * ('''Algorithm-thinking''' skills) Implement the evolutionary algorithms in a programming language of choice (R, Python, or others) | ||
* ('''Probability-thinking''' skills) Obtain probabilities by Monte Carlo simulations | * ('''Probability-thinking''' skills) Obtain probabilities by Monte Carlo simulations | ||
* ('''Population-thinking''' skills) Achieve an algorithmic understanding of major evolutionary processes (drift, mutation, recombination, and natural selection) | |||
* ('''Microbial evolution''') Understand the distinctions between microbial and eukaryotic evolution | * ('''Microbial evolution''') Understand the distinctions between microbial and eukaryotic evolution | ||
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* A textbook on microbial genomics & evolution by the instructor: [https://www.wiley.com/en-us/shop/general-introductory-life-sciences/digital-genomes-monte-carlo-simulations-of-microbes-and-evolution-p-9781394314621 ''Digital Genomes (Qiu 2026)''] | * A textbook on microbial genomics & evolution by the instructor: [https://www.wiley.com/en-us/shop/general-introductory-life-sciences/digital-genomes-monte-carlo-simulations-of-microbes-and-evolution-p-9781394314621 ''Digital Genomes (Qiu 2026)''] | ||
==Assignments, Quizzes, and a Final | ==Assignments, Quizzes, and a Final Presentation== | ||
Student performance will be evaluated by attendance, in-class quizzes and a final presentation | Student performance will be evaluated by attendance, in-class quizzes and a final presentation | ||
* Attendance & participation: | * Attendance & participation: 12 * 5 pts = 60 pts | ||
* Daily assignments: 8 x 10 pts = 80 pts | * Daily assignments: 8 x 10 pts = 80 pts | ||
* Open-Book Quizzes: | * Open-Book Quizzes: 3 x 30 pts = 90 pts | ||
* Final presentation: 30 pts | * Final presentation: 30 pts | ||
Total: | Total: 260 pts | ||
==Course Schedule== | ==Course Schedule== | ||
| Line 43: | Line 44: | ||
====Session 1 (7/13)==== | ====Session 1 (7/13)==== | ||
* Introduction. Lecture slides: [[File:QiuLab-CUNY-Hunter.pdf|thumb]] | * Introduction. Lecture slides: [[File:QiuLab-CUNY-Hunter.pdf|thumb]] | ||
* Gitee accounts & usage | * Gitee accounts & usage; Demo: homework submission using Gitee | ||
* | * Survey 1: Genomics & Data Science | ||
* | * Survey 2: Tree-thinking Skills; Handout: Pre-test 1 | ||
* Lecture: Tree-thinking Skills. | * Lecture: Tree-thinking Skills. | ||
* Assignment 1. Pretest-1. Phylogenetic tree | * <span style="color: green">Assignment 1. Pretest-1. Phylogenetic tree | ||
====Session 2 (7/14)==== | ====Session 2 (7/14)==== | ||
* Install Linux operating systems (Mac OSX or Windows WSL) | * Install Linux operating systems (Mac OSX or Windows WSL) | ||
* Install miniconda & create a new conda environment | * Install miniconda & create a new conda environment | ||
<syntaxhighlight lang=bash> | |||
conda config --add channels defaults | |||
conda config --add channels bioconda | |||
conda config --add channels conda-forge | |||
conda config --set channel_priority strict | |||
conda create -n qiulab perl-bio-bpwrapper | |||
</syntaxhighlight> | |||
* Git usages: Download the course repository: <code>git clone https://gitee.com/huntercollege/comp-genomics-kiz.git</code> | * Git usages: Download the course repository: <code>git clone https://gitee.com/huntercollege/comp-genomics-kiz.git</code> | ||
** Tree manipulations: reroot & tree distances | * Install R, Tidyverse, & Positron | ||
* Tree manipulations: reroot & tree distances | |||
* Gene tree vs Species tree; orthologous and paralogous genes; tree pruning & collapsing | |||
* <span style="color: green">Assignment 2. Tree reroot & gene paralogy | |||
====Session 3 (7/16)==== | ====Session 3 (7/16)==== | ||
* <span style="color: | * Character reconstruction | ||
* | * Phylogenetic analysis: Parsimony analysis | ||
* | * Pre-test 2 | ||
* <span style="color: green">Assignment 3. Parsimony analysis | |||
* To prepare for Quiz 1, review | |||
** Lecture slides: [[File:Phylogeny-lecture-slides-2026.pdf]] | |||
** Three assignments | |||
===Week 2. Linux & Command Line Interface=== | ===Week 2. Linux & Command Line Interface=== | ||
====Session 4 (7/20)==== | ====Session 4 (7/20)==== | ||
* Linux Tutorial I. Basics. [[File:Part-1-intro-unix-2026.pdf|thumb]] | |||
* <span style="color: red">Quiz #1. Phyogenetics | |||
====Session 5 (7/21)==== | ====Session 5 (7/21)==== | ||
* Linux Tutorial II. Advanced | |||
* <span style="color: green">Assignment 4. Linux Intermezzos 1-4 | |||
====Session 6 (7/23)==== | ====Session 6 (7/23)==== | ||
* <span style="color: | * Linux Tutorial III: BpWrapper Toolkit (https://github.com/bioperl/p5-bpwrapper) | ||
* Probability by Monte Carlo simulations | |||
* <span style="color: green">Assignment 5. BbWrapper utilities | |||
===Week 3. Simulations: Central Dogma=== | ===Week 3. Simulations: Central Dogma=== | ||
====Session 7 (7/27)==== | ====Session 7 (7/27)==== | ||
* <span style="color: red">Quiz #2. Linux commands & BpWraper genomics utilities | |||
* The Birthday Problem | |||
** Probability by Monte Carlo simulation | |||
** Simulation algorithms | |||
** Implementation in R or Python | |||
** Visualization | |||
====Session 8 (7/28)==== | ====Session 8 (7/28)==== | ||
* Random DNA sequences | |||
* DNA replication | |||
* DNA transcription | |||
* <span style="color: green">Assignment 6. Implement algorithms & make visualization: B-Day problem; DNA replication & transcription | |||
====Session 9 (7/30)==== | ====Session 9 (7/30)==== | ||
* <span style="color: | * 6-frame translation | ||
** Algorithm | |||
** Visualization | |||
* <span style="color: green">Assignment 7. Implement & Visualize 6-frame translation | |||
===Week 4. Simulations: Population genetics=== | ===Week 4. Simulations: Population genetics=== | ||
====Session 10 (8/3)==== | ====Session 10 (8/3)==== | ||
* Intro: Genetic drift | |||
* <span style="color: red">Quiz #3: Central Dogma | |||
====Session 11 (8/4)==== | ====Session 11 (8/4)==== | ||
* Simulations: Genetic drift | |||
* Simulations: Drift with mutation | |||
* <span style="color: green">Assignment 8 | |||
====Session 12 (8/6)==== | ====Session 12 (8/6)==== | ||
* | * No class (work from home) | ||
* Upload a presentation draft (a tentative title, your name, name of the PI, a 150-words abstract) | |||
===Week 5. | ===Week 5. Final Presentations=== | ||
====Session 13 (8/10)==== | ====Session 13 (8/10)==== | ||
* No class (work from home) | |||
* Upload your 5-slide presentation (in PDF) | |||
====Session 14 (8/11)==== | ====Session 14 (8/11)==== | ||
* Presentations | [[File:KIZ2026-presentation-flyer-4.pdf|thumb|Presentation program]] | ||
* Presentations: Group 1 | |||
====Session 15 (8/13)==== | ====Session 15 (8/13)==== | ||
* Presentations | * Presentations: Group 2 | ||
* Course evaluation | * Course evaluation | ||
Latest revision as of 01:43, 11 August 2026
Professor, Department of Biological Sciences, City University of New York, Hunter College & Graduate Center
Adjunct Faculty, Department of Systems and Computational Biomedicine, Weil Cornell Medical College
Course Overview
Welcome to Computational Genomics, a computer workshop for 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:
- (Tree-thinking skills) Compare and analyze genomes in a phylogenetic framework
- (Algorithm-thinking skills) Implement the evolutionary algorithms in a programming language of choice (R, Python, or others)
- (Probability-thinking skills) Obtain probabilities by Monte Carlo simulations
- (Population-thinking skills) Achieve an algorithmic understanding of major evolutionary processes (drift, mutation, recombination, and natural selection)
- (Microbial evolution) Understand the distinctions between microbial and eukaryotic evolution
Web Links
- Install R base: https://cloud.r-project.org
- Install R Studio (Desktop version): https://docs.posit.co/ide/user/#rstudio-ide-oss-downloads
- R/Tidyverse reference book: R for Data Science (Wickharm et al)
- A textbook on microbial genomics & evolution by the instructor: Digital Genomes (Qiu 2026)
Assignments, Quizzes, and a Final Presentation
Student performance will be evaluated by attendance, in-class quizzes and a final presentation
- Attendance & participation: 12 * 5 pts = 60 pts
- Daily assignments: 8 x 10 pts = 80 pts
- Open-Book Quizzes: 3 x 30 pts = 90 pts
- Final presentation: 30 pts
Total: 260 pts
Course Schedule
Week 1. Intro & Phylogenetics
Session 1 (7/13)
- Introduction. Lecture slides: File:QiuLab-CUNY-Hunter.pdf
- Gitee accounts & usage; Demo: homework submission using Gitee
- Survey 1: Genomics & Data Science
- Survey 2: Tree-thinking Skills; Handout: Pre-test 1
- Lecture: Tree-thinking Skills.
- Assignment 1. Pretest-1. Phylogenetic tree
Session 2 (7/14)
- Install Linux operating systems (Mac OSX or Windows WSL)
- Install miniconda & create a new conda environment
conda config --add channels defaults
conda config --add channels bioconda
conda config --add channels conda-forge
conda config --set channel_priority strict
conda create -n qiulab perl-bio-bpwrapper
- Git usages: Download the course repository:
git clone https://gitee.com/huntercollege/comp-genomics-kiz.git - Install R, Tidyverse, & Positron
- Tree manipulations: reroot & tree distances
- Gene tree vs Species tree; orthologous and paralogous genes; tree pruning & collapsing
- Assignment 2. Tree reroot & gene paralogy
Session 3 (7/16)
- Character reconstruction
- Phylogenetic analysis: Parsimony analysis
- Pre-test 2
- Assignment 3. Parsimony analysis
- To prepare for Quiz 1, review
- Lecture slides: File:Phylogeny-lecture-slides-2026.pdf
- Three assignments
Week 2. Linux & Command Line Interface
Session 4 (7/20)
- Linux Tutorial I. Basics. File:Part-1-intro-unix-2026.pdf
- Quiz #1. Phyogenetics
Session 5 (7/21)
- Linux Tutorial II. Advanced
- Assignment 4. Linux Intermezzos 1-4
Session 6 (7/23)
- Linux Tutorial III: BpWrapper Toolkit (https://github.com/bioperl/p5-bpwrapper)
- Probability by Monte Carlo simulations
- Assignment 5. BbWrapper utilities
Week 3. Simulations: Central Dogma
Session 7 (7/27)
- Quiz #2. Linux commands & BpWraper genomics utilities
- The Birthday Problem
- Probability by Monte Carlo simulation
- Simulation algorithms
- Implementation in R or Python
- Visualization
Session 8 (7/28)
- Random DNA sequences
- DNA replication
- DNA transcription
- Assignment 6. Implement algorithms & make visualization: B-Day problem; DNA replication & transcription
Session 9 (7/30)
- 6-frame translation
- Algorithm
- Visualization
- Assignment 7. Implement & Visualize 6-frame translation
Week 4. Simulations: Population genetics
Session 10 (8/3)
- Intro: Genetic drift
- Quiz #3: Central Dogma
Session 11 (8/4)
- Simulations: Genetic drift
- Simulations: Drift with mutation
- Assignment 8
Session 12 (8/6)
- No class (work from home)
- Upload a presentation draft (a tentative title, your name, name of the PI, a 150-words abstract)
Week 5. Final Presentations
Session 13 (8/10)
- No class (work from home)
- Upload your 5-slide presentation (in PDF)
Session 14 (8/11)
File:KIZ2026-presentation-flyer-4.pdf
- Presentations: Group 1
Session 15 (8/13)
- Presentations: Group 2
- Course evaluation