Southwest-University and EEB BootCamp 2020: Difference between pages

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<center>'''Biomedical Genomics'''</center>
<center>Bioinformatics Boot Camp for Ecology & Evolution: '''Pathogen Evolutionary Genomics'''</center>
<center>July 8-19, 2019</center>
<center>Thursday, Aug 6, 2020, 2 - 3:30pm</center>
<center>'''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 Physiology and Biophysics
<center>'''Instructors:''' Dr Weigang Qiu & Ms Saymon Akther</center>
Institute for Computational Biomedicine, Weil Cornell Medical College</center>
<center>'''Office:''' B402 Belfer Research Building, 413 East 69th Street, New York, NY 10021, USA</center>
<center>'''Email:''' weigang@genectr.hunter.cuny.edu</center>
<center>'''Email:''' weigang@genectr.hunter.cuny.edu</center>
<center>'''Lab Website:''' http://diverge.hunter.cuny.edu/labwiki/</center>
<center>'''Lab Website:''' http://diverge.hunter.cuny.edu/labwiki/</center>
----
<center>
[[File:Lp54-gain-loss.png|200px|thumbnail|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.
* Visualize and explore genomics data using RStudio
* Replicate key results using a raw data set produced by 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==
{| class="wikitable"
{| class="wikitable"
|-
|-
! Date & Hour !! Tutorial/Lecture !! Paper !! Quiz/Exam
! Lyme Disease (Borreliella) !! CoV Genome Tracker !! Coronavirus evolutuon
|-
| July 8 (Mon), 8:40-12:10 || Introduction/R Tutorial I/NGS || Paper 1 ||
|-
| July 9 (Tu), 8:40-12:10 || NGS/R Tutorial II || Paper 1 (cont'd) ||
|-
| July 10 (Wed), 8:40-12:10 || Genome analysis/R Tutorial III || Paper 2 || Quiz I
|-
| July 11 (Thur), 8:40-12:10 || Genome analysis/R Tutorial IV || Paper 2 (cont'd) ||
|-
| July 12 (Fri), 8:40-12:10 || Transcriptome analysis || Paper 3 || Mid-term Exam
|-
| July 15 (Mon), 8:00-12:10 || Transcriptome analysis || Paper 3 (cont'd) ||
|-
| July 16 (Tu), 8:00-12:10 || Microbiome analysis || Paper 4 || Quiz II
|-
| July 17 (Wed), 8:00-12:10 || Microbial genomics || Paper 5 ||
|-
| July 18 (Thur), 8:00-12:10 || Human genomic variations || Paper 5 (cont'd) || Presentation I
|-
|-
| July 19 (Fri), 8:00-12:10|| Example || Example || Presentation II
| [[File:Lp54-gain-loss.png|300px|thumbnail| Gains & losses of host-defense genes among Lyme pathogen genomes (Qiu & Martin 2014)]] ||
[[File:Cov-screenshot-1.png|300px|thumbnail| [http://cov.genometracker.org/ Haplotype network] ]]
||  
[[File:Cov-screenshot-2.png|300px|thumbnail| Spike protein alignment ]]
|}
|}
</center>
----
==Case studies from Qiu Lab==
* [http://borreliabase.org Comparative genomics of worldwide Lyme disease pathogens]
* [http://cov.genometracker.org Covid-19 Genome Tracker]
==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]


==Papers & Data==
==Tutorial==
{| class="wikitable sortable"
* 2-2:30: Introduction on pathogen phylogenomics
|-
* 2:30-2:45: data pre-processing with BpWrapper
! Omics Application !! Paper link !! Data set !! NGS Technology
* 2:45-3:00: build haplotype network with TCS
|-
* 3:00-3:15: interactive visualization with BuTCS
| Microbiome || [https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0193652 Rimoldi_etal_2018_PlosOne] || [https://doi.org/10.1371/journal.pone.0193652.s004 S1 Dataset] || 16S rDNA amplicon sequencing
* 3:15-3:30: Q & A
|-
| Transcriptome || [https://science.sciencemag.org/content/350/6264/1096 Wang_etal_2015_Science] || Tables S2 & S4 || RNA-Seq
|-
| Transcriptome & Regulome || [https://bmcmedgenomics.biomedcentral.com/articles/10.1186/s12920-019-0477-8 Nava_etal_2019_BMCGenomics] || Tables S2 & S3 || RNA-Seq & CHIP-Seq
|-
| Proteome || [https://www.ncbi.nlm.nih.gov/pubmed/28232952 Qiu_etal_2017_NPJ] || (to be posted) || SILAC
|-
| Population genomics (Lyme) || [https://jcm.asm.org/content/56/11/e00940-18.long Di_etal_2018_JCM] || [https://github.com/weigangq/ocseq Data & R codes] || Amplicon sequencing (antigen locus)
|-
| Population genomics/GWAS (Human) || [https://science.sciencemag.org/content/351/6274/737.long Simonti_etal_2016_Science] || [https://science.sciencemag.org/highwire/filestream/673591/field_highwire_adjunct_files/1/aad2149-Simonti-SM.Table.S2.xlsx Table S2] || whole-genome sequencing (WGS); [http://www.internationalgenome.org/ 1000 Genome Project (IGSR)]
|-
| TB surveillance || [https://jcm.asm.org/content/53/7/2230 Brow_etal_2015]  || [https://www.ebi.ac.uk/ena/data/view/PRJEB9206 Sequence Archives]|| Whole-genome sequencing (WGS)
|-
| Example || Example || Example || Example
|-
| Example || Example || Example || Example
|-
| Example || Example || Example || Example
|}

Revision as of 06:50, 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

Bioinformatics Tools & Learning Goals

Tutorial

  • 2-2:30: Introduction on pathogen phylogenomics
  • 2:30-2:45: data pre-processing with BpWrapper
  • 2:45-3:00: build haplotype network with TCS
  • 3:00-3:15: interactive visualization with BuTCS
  • 3:15-3:30: Q & A