BioMed-R-2020 and EEB BootCamp 2020: Difference between pages

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<center>'''BIOL47120 Biomedical Genomics II'''</center>
<center>Bioinformatics Boot Camp for Ecology & Evolution: '''Pathogen Evolutionary Genomics'''</center>
<center>Spring 2020, Saturdays 9-12 noon, Hunter North Building 1001G</center>
<center>Thursday, Aug 6, 2020, 2 - 3:30pm</center>
<center>'''Instructor:''' Weigang Qiu, Ph.D., Professor, Department of Biological Sciences, Hunter College, CUNY; '''Email:''' weigang@genectr.hunter.cuny.edu</center>
<center>'''Instructors:''' Dr Weigang Qiu & Ms Saymon Akther</center>
<center>'''T.A.:''' Christopher Panlasigui; Hunter College; '''Email:''' christopher.panlasigui47@myhunter.cuny.edu</center>
<center>'''Email:''' weigang@genectr.hunter.cuny.edu</center>
<center>'''Office:''' B402 Belfer Research Building, 413 East 69th Street, New York, NY 10021, USA; '''Office hour''': Wed 3-5pm</center>
<center>'''Lab Website:''' http://diverge.hunter.cuny.edu/labwiki/</center>
<center>
<center>
{| class="wikitable"
{| class="wikitable"
|-
|-
! MA plot !! Volcano plot !! Heat map
! Lyme Disease (Borreliella) !! CoV Genome Tracker !! Coronavirus evolutuon
|-
|-
| [[File:GeneExp1.jpeg|300px|thumbnail| fold change (y-axis) vs. total expression levels (x-axis)]] ||  
| [[File:Lp54-gain-loss.png|300px|thumbnail| Gains & losses of host-defense genes among Lyme pathogen genomes (Qiu & Martin 2014)]] ||  
[[File:GeneExp2.jpeg|300px|thumbnail| p-value (y-axis) vs. fold change (x-axis)]]
[[File:Cov-screenshot-1.png|300px|thumbnail| [http://cov.genometracker.org/ Haplotype network] ]]
||  
||  
  [[File:GeneExp3.jpeg|300px|thumbnail| genes significantly down or up-regulated (at p<1e-4)]]
  [[File:Cov-screenshot-2.png|300px|thumbnail| Spike protein alignment ]]
|}
|}
</center>
</center>
==Course Overview==
----
Welcome to Introductory BioMedical Genomics, a seminar course 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 rapid DNA and RNA-sequencing  technologies, biomedical sciences are undergoing a rapid & irreversible transformation into a highly data-intensive field, that requires familiarity  with concepts in both biology, computational, and data sciences. 


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 statistics.  
==Case studies from Qiu Lab==
* [http://borreliabase.org Comparative genomics of worldwide Lyme disease pathogens]
* [http://cov.genometracker.org Covid-19 Genome Tracker]


This workshop is designed to introduce computational analysis of genomic data through hands-on computational exercises. Students are expected to be able to replicate key results of data analysis from published studies.
==CoV genome data set==
* N=565 SARS-CoV-2 genomes collected during January & February 2020. Data source & acknowledgement [http://gisaid.org GIDAID] (<em>Warning: You need to acknowledge GISAID if you reuse the data in any publication</em>)
* Download file: [http://diverge.hunter.cuny.edu/~weigang/qiu-akther.tar.gz data file]
* Create a directory, unzip, & un-tar
<syntaxhighlight lang='bash'>
mkdir QiuAkther
mv cov-camp.tar.gz QiuAkther/
cd QiuAkther
tar -tzf cov-camp.tar.gz # view files
tar -xzf cov-camp.tar.gz # un-zip & un-tar
</syntaxhighlight>
* View files
<syntaxhighlight lang='bash'>
file TCS.jar
ls -lrt # long list, in reverse timeline
less Jan-Feb.mafft # an alignment of 565 CoV2 genomes in FASTA format; "q" to quit
less cov-565strains-617snvs.phy # non-gapped SNV alignment in PHYLIP format
wc hap.txt # geographic origins
head hap.txt
wc group.txt # color assignment
cat group.txt
less cov-565strains.gml # graph file (output)
</syntaxhighlight>


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.
==Bioinformatics Tools & Learning Goals==
* BpWrapper: commandline tools for sequence, alignment, and tree manipulations (based on BioPerl).
** [https://github.com/bioperl/p5-bpwrapper Github Link]
** [https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-018-2074-9/figures/1 Flowchart from publication]
* Haplotype network with TCS [https://pubmed.ncbi.nlm.nih.gov/11050560/ PubMed link]
* Web-interactive visualization with [http://D3js.org D3js]
** [https://github.com/sairum/tcsBU Github link]
** [https://cibio.up.pt/software/tcsBU/index.html Web tool]
** [https://academic.oup.com/bioinformatics/article/32/4/627/1744448 Paper]


==Learning goals==
==Tutorial==
By the end of this course successful students will be able to:
* 2-2:30: Introduction on pathogen phylogenomics
* Describe next-generation sequencing  (NGS) technologies & contrast it with traditional Sanger sequencing
* 2:30-2:45: Demo: sequence manipulation with BpWrapper
* Explain applications of NGS technology including pathogen genomics, cancer genomics, human genomic variation, transcriptomics, meta-genomics, epi-genomics, and microbiome.
<syntaxhighlight lang='bash'>
* Visualize and explore genomics data using R & RStudio
bioseq --man
* Replicate key results using a raw data set produced by a primary research paper
bioseq -n Jan-Feb.mafft
 
bioaln --man
==Web Links==
bioaln -n -i'fasta' Jan-Feb.mafft
* Install R base: https://cloud.r-project.org
bioaln -l -i'fasta' Jan-Feb.mafft
* Install R Studio (Desktop version): http://www.rstudio.com/download
bioaln -n -i'phylip' cov-565strains-617snvs.phy
* Textbook: [http://r4all.org/#about Introduction to R for Biologists]
bioaln -l -i'phylip' cov-565strains-617snvs.phy
* Download: [http://www.r4all.org/books/datasets R datasets]
FastTree -nt cov-565strains-617snvs.phy > cov.dnd
* A reference book: [https://r4ds.had.co.nz/ R for Data Science (Wickharm & Grolemund)]
biotree --man
 
biotree -n cov.dnd
==Quizzes and Exams==
biotree -l cov.dnd
Student performance will be evaluated by attendance, weekly assignments, quizzes, and a final report:
<syntaxhighlight>
* Attendance & In-class participation: 50 pts
* 2:45-3:00: build haplotype network with TCS
* Assignments: 5 x 10 = 50 pts
<syntaxhighlight lang='bash'>
* Quizzes: 2 x 25 pts = 50 pts
java -jar -Xmx1g TCS.jar
* Mid-term: 50 pts
<syntaxhighlight>
* Final presentation & report: 100 pts
* 3:00-3:15: interactive visualization with BuTCS
Total: 300 pts
* 3:15-3:30: Q & A
 
==Tips for Success==
To maximize the your experience we strongly recommend the following strategies:
* Follow the directions for efficiently, finding high-impact papers, reading science research papers and preparing presentations.  
* Read the papers, watch required videos and do the exercises regularly, long before you attend class.
* Attend all classes, as required.  Late arrival results in loss of points.
* Keep up with online exercises. Don’t wait until the due date to start tasks.
* Take notes or annotate slides while attending the lectures.
* Listen actively and participate in class and in online discussions. 
* Review and summarize material within 24 hrs after class.
* Observe the deadlines for submitting your work. Late submissions incur penalties.
* Put away cell phones, do not TM, email or play computer games in class.
 
==Hunter/CUNY Policies==
* Policy on Academic Integrity
Hunter College regards acts of academic dishonesty (e.g., plagiarism, cheating on homework, online exercises or examinations, obtaining unfair advantage, and falsification of records and official documents) as serious offenses against the values of intellectual honesty.  The College is committed to enforcing the CUNY Policy on Academic Integrity, and we will pursue cases of academic dishonesty according to the Hunter College Academic Integrity Procedures.  Students will be asked to read this statement before exams.
 
* ADA Policy
In compliance with the American Disability Act of 1990 (ADA) and with Section 504 of the Rehabilitation Act of 1973, Hunter College is committed to ensuring educational parity and accommodations for all students with documented disabilities and/or medical conditions. It is recommended that all students with documented disabilities (Emotional, Medical, Physical, and/or Learning) consult the Office of AccessABILITY, located in Room E1214B, to secure necessary academic accommodations. For further information and assistance, please call: (212) 772- 4857 or (212) 650-3230.
 
* Syllabus Policy
Except for changes that substantially affect implementation of the evaluation (grading) statement, this syllabus is a guide for the course and is subject to change with advance notice, announced in class or posted on Blackboard.
 
==Course Schedule==
===Feb 1, 2020===
* Introduction
* R Tutorial 1: Use interface, basic operations, load data. Slides: [[File:R-part-1.pdf|thumbnail]]
{| class="wikitable sortable mw-collapsible"
! Assignment 1 (10 pts; Due next class 2/8, in hard copy)
|-
|
* (3 pts) Print a copy of your first R script, with proper annotations
* (3 pts) Transform the following "untidy/wide" table into a "tidy/tall" table (print a hard copy)
<pre>
PropertyName,Density_250m,Density_500m,Density_1000m
HighbridgePark,0.006561319,0.009462031,0.010578611
BronxRiverParkway,0.001318749,0.001978858,0.002652118
CrotonaPark,0.009412087,0.01164712,0.01202321
ClaremontPark,0.016391948,0.019972485,0.020350481
VanCortlandtPark,0.000550151,0.000979312,0.001372675
</pre>
* (4 pts) Make a single slide of a primary research paper using next-generation sequencing (NGS) technologies, show the following
** proper citation (authors, title, year, journal, URL)
** NGS method (Illumina, PacBio, or NanoPore)
** NGS application (genomics, cancer, transcriptome, microbiome, proteome, metagenomics, human variation, etc)
** a key figure, with a caption explaining x-axis, y-axis, samples, experiments
** raw data table (show first few columns and first few rows)
** for example, a student has worked on tissue regeneration, the search in PubMed with key words "regeneration zebra fish transcriptome" found the following primary paper as the best because of the high quality of journal and the availability of raw data: https://www.ncbi.nlm.nih.gov/pubmed/28096348
|}
 
===Feb 8, 2019===
* Introduction to NGS: [[File:Intro-NGS.pdf|thumbnail]]
* 1-slide presentations on Next-Generation Sequencing Technologies (Group I)
* R Tutorial, Part 2. Data manipulation with dplyr. Slides: [[File:R-tutorials-2.pdf|thumbnail]]
{| class="wikitable sortable mw-collapsible"
! Assignment 1 (10 pts; Due next class 2/15, in hard copy)
|-
|
* (3 pts) Print a copy of your 2nd R script, with proper annotations
* (4 pts) Show following commands with the chaining operator ("%>%") for the "iris" data set:
** Select columns "Sepal.Length" & "Species"
** Filter rows 2 through 10
** Add a column "logSepalLength" by taking the logarithm of the said column
** Calculate mean and standard deviation of Petal.Length in each species
* (3 pts) Transform the "iris" data table into a "tidy/tall" table (manually, show first 10 rows, print a hard copy)
|}
 
===Feb 15, 2019===
* NGS presentations (Group II)
* R Tutorial. Chapter 4. Data visualization with ggplot2. Slides: to be posted
* Assignment 3: to be posted
 
===Feb 22, 2019===
* Group assignments for research/application papers: Each student should search the PubMed and identify one primary research paper for a 5-slide presentation next week
** Bacterial genomics
** Metagenomics
** Microbiome
** Cancer genomics
** Chip-Seq
** Human genome
** RNA-Seq
** Signle Cell transcriptome
* R tutorial: Chapter 4. Data visualization with ggplot2
* Assignment #4
 
===Feb 29, 2019===
* 5-slide presentation on selected paper, including Objective/Goal, Material & Methods, Main results (you want to replicate), & Available data sets and scripts
* Review for mid-term
===March 7, 2019===
* Mid-term exam, including
** NGS terms & vocabulary
** Advantages of NGS over traditional Sanger sequencing
** R practicum: read data table into R; make tall tables; manipulation of data frame with dplyr; basic plots with ggplot2
** Revise/Refine your last presentation by including the following parts:
*** Title slide: Paper citation, web links, group member names, date, version
*** Background/Objectives: 1 slide
*** Experimental samples & methods: 1-2 slides (including NGS tech used)
*** Analytical methods: software, main statistical methods (e.g., type of graphs, tests, and p-value interpretation)
*** Results: 1-2 graphs
*** Conclusion: 1 slide
*** Supplemental Material: 1 data set you will be re-analyzing
*** Analytical plan: type of graphs & type of statistical tests
 
===March 14, 2019===
* R tutorial: Section 5.2. Contingency analysis
* Group presentations (Data set identified)
===March 22, 2019===
* R tutorial: Section 5.3. t-test
* Group presentations (Data visualization)
===March 28, 2019===
* (Self study; No live class)
* Abstract (200 words; individualized; due 3/30)
* Review contingency test & two-sample t-test
* Generate preliminary graphs
 
===March 30, 2019===
* 20 pts Quiz on contingency test & two-sample t-test
* Group presentations (Show preliminary graphs)
* Material & Methods (due 4/6)
 
===April 4, 2019===
* 20 pts Quiz
* R tutorial: Section 5.4. Regression analysis
* Results (due 4/13)
** Tables to show the dataset you work on (not all, but a sample)
** Figures with legend (R methods, x & y-axis, conclusion)
** 1-paragraph summary of your results
 
===April 18, 2019===
* 20 pts Quiz. Regression analysis
* Background & Introduction (due 5/4)
 
===April 25, 2019===
* Final presentation I. Graded on:
** Objective (original & your own)
** Material & methods (original & your own)
** Results (your own)
** Conclusion (your own)
** Conclusion (due 5/11)
 
===May 2, 2019===
* Self study: Prepare your 10-slide presentation
* No class (instructor travels)
===May 16, 2019, 9-1pm===
* Final presentation
* May 22, 2018 (Wed, 5pm) Final Report Due (hard copy; n my office or in mailbox)

Revision as of 07:23, 26 July 2020

Bioinformatics Boot Camp for Ecology & Evolution: Pathogen Evolutionary Genomics
Thursday, Aug 6, 2020, 2 - 3:30pm
Instructors: Dr Weigang Qiu & Ms Saymon Akther
Email: weigang@genectr.hunter.cuny.edu
Lab Website: http://diverge.hunter.cuny.edu/labwiki/
Lyme Disease (Borreliella) CoV Genome Tracker Coronavirus evolutuon
Gains & losses of host-defense genes among Lyme pathogen genomes (Qiu & Martin 2014)
Spike protein alignment

Case studies from Qiu Lab

CoV genome data set

  • N=565 SARS-CoV-2 genomes collected during January & February 2020. Data source & acknowledgement GIDAID (Warning: You need to acknowledge GISAID if you reuse the data in any publication)
  • Download file: data file
  • Create a directory, unzip, & un-tar
mkdir QiuAkther
mv cov-camp.tar.gz QiuAkther/
cd QiuAkther
tar -tzf cov-camp.tar.gz # view files
tar -xzf cov-camp.tar.gz # un-zip & un-tar
  • View files
file TCS.jar
ls -lrt # long list, in reverse timeline
less Jan-Feb.mafft # an alignment of 565 CoV2 genomes in FASTA format; "q" to quit
less cov-565strains-617snvs.phy # non-gapped SNV alignment in PHYLIP format
wc hap.txt # geographic origins
head hap.txt
wc group.txt # color assignment
cat group.txt
less cov-565strains.gml # graph file (output)

Bioinformatics Tools & Learning Goals

Tutorial

  • 2-2:30: Introduction on pathogen phylogenomics
  • 2:30-2:45: Demo: sequence manipulation with BpWrapper

<syntaxhighlight lang='bash'> bioseq --man bioseq -n Jan-Feb.mafft bioaln --man bioaln -n -i'fasta' Jan-Feb.mafft bioaln -l -i'fasta' Jan-Feb.mafft bioaln -n -i'phylip' cov-565strains-617snvs.phy bioaln -l -i'phylip' cov-565strains-617snvs.phy FastTree -nt cov-565strains-617snvs.phy > cov.dnd biotree --man biotree -n cov.dnd biotree -l cov.dnd <syntaxhighlight>

  • 2:45-3:00: build haplotype network with TCS

<syntaxhighlight lang='bash'> java -jar -Xmx1g TCS.jar <syntaxhighlight>

  • 3:00-3:15: interactive visualization with BuTCS
  • 3:15-3:30: Q & A