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>'''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.  
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==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
* ('''Pop Gen''') Achieve an algorithmic understanding of major evolutionary processes (drift, mutation, recombination, and natural selection)
* Program in Python for parsing texts and simulating evolution
* ('''Computation''') Implement the evolutionary algorithms in a programming language of choice (R, Python, or others)
* Visualize data and perform statistical analysis using R/RStudio
* ('''Phylogenomics''') Compare and analyze genomes in a phylogenetic framework
* Compose a bioinformatics research report
* ('''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): http://www.rstudio.com/download
* 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, three (3) quizzes and a final presentation
* Attendance & participation: 60 pts
* Attendance & participation: 12 * 5 pts = 60 pts
* Daily assignments:  8 x 10 pts  = 80 pts
* Open-Book Quizzes: 3 x 30 pts = 60 pts
* Open-Book Quizzes: 3 x 30 pts = 60 pts
* Final presentation: 30 pts
* Final presentation: 30 pts
Total: 150 pts
Total: 230 pts


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


====Session 2, 7/14 (Tuesday)====
====Session 2, 7/14 (Tuesday)====
* Git usages (by Mr Liu)
* Git usages (by Mr Liu)
** Demo: homework submission using Gitee
** Download the course repository: <code>git clone https://gitee.com/huntercollege/comp-genomics-kiz.git</code>  
** Download the course repository: <code>git clone https://gitee.com/huntercollege/comp-genomics-kiz.git</code>  
* Linux Tutorial I. [[File:Intro-unix-KIZ.pdf|thumb]]
* Linux Tutorial I. [[File:Intro-unix-KIZ.pdf|thumb]]
* Phylogenetics lecture: [[File:Part-1-tree-thinking.pdf|thumb]]
** Tree manipulations: reroot & tree distances
** Tree manipulations: reroot & tree distances
** Gene tree vs Species tree; orthologous and paralogous genes; tree pruning & collapsing
** Gene tree vs Species tree; orthologous and paralogous genes; tree pruning & collapsing


====Session 3, 7/16 (Thursday)====
====Session 3, 7/16 (Thursday)====
* Review: Tree manipulations
* <span style="color: red">Quiz #1. tree terms & tree manipulations</span> (20 pts); open-book
* <span style="color: red">Quiz #1. tree terms & tree manipulations</span> (20 pts); open-book; 9-10am, in-class
* <span style="color: green">Linux Tutorial II: BpWrapper Toolkit (https://github.com/bioperl/p5-bpwrapper)</span> Updated sldies: [[File:Intro-unix-KIZ.pdf|thumb]]
* <span style="color: green">Linux Tutorial II: BpWrapper Toolkit (https://github.com/bioperl/p5-bpwrapper)</span> Updated sldies: [[File:Intro-unix-KIZ.pdf|thumb]]


===Week 4, Thursday, Oct 31, 2024 (Halloween)===
===Week 2===
* <span style="color: red">Quiz #2. Linux commands & BpWrappper toolkits</span>: 20 pts, 9-10:30am
===Week 3===
* <span style="color: orange">AFSV Genomics I </span>: Download and align genomes.
===Week 4===
** Fork a copy of [https://edu.gitee.com/huntercollege/projects/696311/repos/huntercollege/afsv-genomics/sources the ASFV project repository].
====Session 13 (8/10)====
** Instructions to fork a repository (prepared by Mr Liu): https://zwmqn249t3y.feishu.cn/wiki/OVdEwB00ciNx9Xkxvxsc7lJEncc?from=from_copylink
====Session 14 (8/11)====
** Project overview: Lecture slides: [[File:Afsv-project-kiz.pdf|thumb]]
* Presentations
 
====Session 15 (8/13)====
===Week 5, Thursday, Nov 7, 2024===
* Presentations
* ASFV project:
** <code> git clone https://gitee.com/huntercollege/asfv-genomics.git </code>
** Align genomes: protocol-1
** SNP calls; quality check by Ts/Tv ratio (Protocol 1)
** 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===
* 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]]
* Assignment: Practice-1 & -2
 
===Week 7, Thursday, Nov 21, 2024===
* R Tutorial 2. Data visualization & statistics. Slides: [[File:R-tutorials-KIZ-part-2.pdf|thumb]]
** Assignment: Practice-3 & -4
* Final project:
** Introduction to Ka/Ks analysis
** 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)===
* R Tutorial 3. [https://borreliabase.org/~wgqiu/r-demo-2024.html Cluster analysis]:
** Part 4. Heatmap (hierarchical clustering) & principal component analysis (PCA)
** Part 5. Gene expression analysis.
** Assignment: reproduce the cluster analysis
* Final project: [https://borreliabase.org/~wgqiu/asfv-genomics-visual.html R Markdown Demo]
** 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

Revision as of 15:56, 12 July 2026

Banner-comp-genomics.png
2-5pm, July 13 - Aug 13, 2026
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:

  • (Pop Gen) Achieve an algorithmic understanding of major evolutionary processes (drift, mutation, recombination, and natural selection)
  • (Computation) Implement the evolutionary algorithms in a programming language of choice (R, Python, or others)
  • (Phylogenomics) Compare and analyze genomes in a phylogenetic framework
  • (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, three (3) 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 = 60 pts
  • Final presentation: 30 pts

Total: 230 pts

Course Schedule

Week 1

Session 1, 7/13 (Monday)

Session 2, 7/14 (Tuesday)

Session 3, 7/16 (Thursday)

Week 2

Week 3

Week 4

Session 13 (8/10)

Session 14 (8/11)

  • Presentations

Session 15 (8/13)

  • Presentations
  • Course evaluation
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