Computational Genomics Summer 2026: Difference between revisions

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(Created page with "800px|center <center>9-12 noon, July 13 - Aug 6, 2026</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</cente...")
 
 
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[[File:Banner-comp-genomics.png|800px|center]]
[[File:Banner-comp-genomics.png|800px|center]]
<center>9-12 noon, July 13 - Aug 6, 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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----
----
==Course Overview==
==Course Overview==
Welcome to Computational Genomics, a 9-week 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.  
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.  
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.  
Line 19: Line 20:
==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:  
* Use Linux commands & compose simple shell scripts to automate a bioinformatics pipeline
* ('''Tree-thinking''' skills) Compare and analyze genomes in a phylogenetic framework
* Program in Python for parsing texts and simulating evolution
* ('''Algorithm-thinking''' skills) Implement the evolutionary algorithms in a programming language of choice (R, Python, or others)
* Visualize data and perform statistical analysis using R/RStudio
* ('''Probability-thinking''' skills) Obtain probabilities by Monte Carlo simulations
* Compose a bioinformatics research report
* ('''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==
==Web Links==
* Install R base: https://cloud.r-project.org
* Install R base: https://cloud.r-project.org
* Install R Studio (Desktop version): http://www.rstudio.com/download
* Install R Studio (Desktop version): https://docs.posit.co/ide/user/#rstudio-ide-oss-downloads
* Download: [http://www.r4all.org/books/datasets R datasets]
* R/Tidyverse reference book: [https://r4ds.hadley.nz/ R for Data Science (Wickharm et al)]
* A reference book: [https://r4ds.hadley.nz/ R for Data Science (Wickharm et al)]
* 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)'']
* Github repository: [https://github.com/weigangq/CSB-BIOL425/tree/master/lecture-materials Computational Skills for Biologists (Allesina & Wilmes)]


==Assignments, Quizzes, and Final Report==
==Assignments, Quizzes, and a Final Presentatio8n==
Student performance will be evaluated by attendance, three (3) quizzes and a final presentation
Student performance will be evaluated by attendance, in-class quizzes and a final presentation
* Attendance & participation: 60 pts
* Attendance & participation: 14 * 5 pts = 70 pts
* Open-Book Quizzes: 3 x 30 pts = 60 pts
* Daily assignments:  8 x 10 pts  = 80 pts
* Open-Book Quizzes: 4 x 30 pts = 120 pts
* Final presentation: 30 pts
* Final presentation: 30 pts
Total: 150 pts
Total: 300 pts


==Course Schedule==
==Course Schedule==
===Week 1===
===Week 1. Intro & Phylogenetics===
====Session 1, 7/13 (Monday)====
====Session 1 (7/13)====
* Introudction. Lecture slides: [[File:QiuLab-CUNY-Hunter.pdf|thumb]]
* Introduction. Lecture slides: [[File:QiuLab-CUNY-Hunter.pdf|thumb]]
* Computer setup: gitee accounts (for course management). [https://edu.gitee.com/huntercollege/courses/3030/noticeboard Course link on gitee]
* Gitee accounts & usage; Demo: homework submission using Gitee
* <span style="color: blue">Survey 1: Genomics & Data Science</span> PDF file: [[File:KIZ-survey-1.pdf|thumb]]
* Survey 1: Genomics & Data Science  
* <span style="color: blue">Survey 2: Tree-thinking Skills</span> PDF file: [[File:Pretest-1.pdf|thumb]]
* Survey 2: Tree-thinking Skills; Handout: Pre-test 1
* Computer setup: Linux accounts (on the "phylonet.net" server)
* Lecture: Tree-thinking Skills.  
* Lecture: Tree-thinking Skills. Lecture slides: [[File:Phylogeny-lecture-slides-2024.pdf]]
* <span style="color: green">Assignment 1. Pretest-1. Phylogenetic tree


====Session 2, 7/14 (Tuesday)====
====Session 2 (7/14)====
* Git usages (by Mr Liu)
* Install Linux operating systems (Mac OSX or Windows WSL)
** Demo: homework submission using Gitee
* Install miniconda & create a new conda environment
** Download the course repository: <code>git clone https://gitee.com/huntercollege/comp-genomics-kiz.git</code>  
<syntaxhighlight lang=bash>
* Linux Tutorial I. [[File:Intro-unix-KIZ.pdf|thumb]]
conda config --add channels defaults
* Phylogenetics lecture: [[File:Part-1-tree-thinking.pdf|thumb]]
conda config --add channels bioconda
** Tree manipulations: reroot & tree distances
conda config --add channels conda-forge
** Gene tree vs Species tree; orthologous and paralogous genes; tree pruning & collapsing
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>
* 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 (Thursday)====
====Session 3 (7/16)====
* Review: Tree manipulations
* Character reconstruction
* <span style="color: red">Quiz #1. tree terms & tree manipulations</span> (20 pts); open-book; 9-10am, in-class
* Phylogenetic analysis: Parsimony analysis
* <span style="color: green">Linux Tutorial II: BpWrapper Toolkit (https://github.com/bioperl/p5-bpwrapper)</span> Updated sldies: [[File:Intro-unix-KIZ.pdf|thumb]]
* 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 4, Thursday, Oct 31, 2024 (Halloween)===
===Week 2. Linux & Command Line Interface===
* <span style="color: red">Quiz #2. Linux commands & BpWrappper toolkits</span>: 20 pts, 9-10:30am
====Session 4 (7/20)====
* <span style="color: orange">AFSV Genomics I </span>: Download and align genomes.
* Linux Tutorial I. Basics. [[File:Part-1-intro-unix-2026.pdf|thumb]]
** Fork a copy of [https://edu.gitee.com/huntercollege/projects/696311/repos/huntercollege/afsv-genomics/sources the ASFV project repository].
* <span style="color: red">Quiz #1. Phyogenetics
** Instructions to fork a repository (prepared by Mr Liu): https://zwmqn249t3y.feishu.cn/wiki/OVdEwB00ciNx9Xkxvxsc7lJEncc?from=from_copylink
** Project overview: Lecture slides: [[File:Afsv-project-kiz.pdf|thumb]]


===Week 5, Thursday, Nov 7, 2024===
====Session 5 (7/21)====
* ASFV project:
* Linux Tutorial II. Advanced
** <code> git clone https://gitee.com/huntercollege/asfv-genomics.git </code>
====Session 6 (7/23)====
** Align genomes: protocol-1
* Linux Tutorial III: BpWrapper Toolkit (https://github.com/bioperl/p5-bpwrapper)
** SNP calls; quality check by Ts/Tv ratio (Protocol 1)
* Probability by Monte Carlo simulations
** Annotate SNPs: Protocol 2
** IQ-tree to get genome tree: Protocol-3
* Trait evolution and comparative analysis [[File:Trait-evolution-KIZ.pdf|thumb]]
* Assignment: Pre-test 2


===Week 6, Thursday, Nov 14, 2024===
===Week 3. Simulations: Central Dogma===
* Computer setup: R & RStudio; <span style="color: orange">R Tutorial Part 1: Basic R & Data manipulations</span>. Lecture slides [[File:R-tutorials-KIZ-part-1.pdf|thumb]]
====Session 7 (7/27)====
* Assignment: Practice-1 & -2
* <span style="color: red">Quiz #2
====Session 8 (7/28)====
====Session 9 (7/30)====
* <span style="color: red">Quiz #3


===Week 7, Thursday, Nov 21, 2024===
===Week 4. Simulations: Population genetics===
* R Tutorial 2. Data visualization & statistics. Slides: [[File:R-tutorials-KIZ-part-2.pdf|thumb]]
====Session 10 (8/3)====
** Assignment: Practice-3 & -4
====Session 11 (8/4)====
* Final project:
====Session 12 (8/6)====
** Introduction to Ka/Ks analysis
* <span style="color: red">Quiz #4
** File distribution: each student is assigned 10 random genes; Run <code>git pull</code>; or if you haven't cloned the repository, run <code>git clone https://gitee.com/huntercollege/asfv-genomics.git</code>
** Follow the protocol in "doc/protocol-4-paml.txt"


===Week 8, Thursday, Nov 28, 2024 (Thanksgiving)===
===Week 5. Microbial genomics===
* R Tutorial 3. [https://borreliabase.org/~wgqiu/r-demo-2024.html Cluster analysis]:
====Session 13 (8/10)====
** Part 4. Heatmap (hierarchical clustering) & principal component analysis (PCA)
====Session 14 (8/11)====
** Part 5. Gene expression analysis.
* Presentations
** Assignment: reproduce the cluster analysis
====Session 15 (8/13)====
* Final project: [https://borreliabase.org/~wgqiu/asfv-genomics-visual.html R Markdown Demo]
* Presentations
** Visualize tree with <code>ggtree</code>
** Plot Ka/Ks for genes
** Run IQ-TREE to obtain site-specific rates; Plot site-specific rates
 
===Week 9, Thursday, Dec 5, 2024===
* Final presentations: student demos & trouble shooting
 
===Week 10, Thursday, Dec 10, 2024===
* ASFV project overview slides: [[File:Asfv-project-kiz-Dec-5-2024.pdf|thumb]]
* Final presentations (30 pts):
** (10 pts) 3 slides & 5 min
** (15 pts) Show & interpret results for a single gene (no need to show all genes on PPT, although you will upload all MLC and tree files). Pick a genes that is the most interesting to you (e.g., significant position selection, apparent inconsistency with the genome tree, important gene function, etc).
** (5 pts) Conclusions & future directions. Find gene name and function from this paper: https://www.mdpi.com/2076-2615/14/15/2187 (you need to first find the gene name using the "BA71.gff3" file with <code>grep</code>)
* Course evaluation
* Course evaluation

Latest revision as of 05:59, 20 July 2026

Banner-comp-genomics.png
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

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

Assignments, Quizzes, and a Final Presentatio8n

Student performance will be evaluated by attendance, in-class quizzes and a final presentation

  • Attendance & participation: 14 * 5 pts = 70 pts
  • Daily assignments: 8 x 10 pts = 80 pts
  • Open-Book Quizzes: 4 x 30 pts = 120 pts
  • Final presentation: 30 pts

Total: 300 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

Week 2. Linux & Command Line Interface

Session 4 (7/20)

Session 5 (7/21)

  • Linux Tutorial II. Advanced

Session 6 (7/23)

Week 3. Simulations: Central Dogma

Session 7 (7/27)

  • Quiz #2

Session 8 (7/28)

Session 9 (7/30)

  • Quiz #3

Week 4. Simulations: Population genetics

Session 10 (8/3)

Session 11 (8/4)

Session 12 (8/6)

  • Quiz #4

Week 5. Microbial genomics

Session 13 (8/10)

Session 14 (8/11)

  • Presentations

Session 15 (8/13)

  • Presentations
  • Course evaluation
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