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Microbiome analysis using 2nd and 3rd generation DNA sequencing + multivariate data analysis (5.5 ECTS) - 2019
Provider: Faculty of Science

Activity no.: 5325-19-04-31There are no available seats 
Enrollment deadline: 04/05/2019
PlaceDepartment of Food Science
Date and time18.03.2019, at: 08:30 - 26.03.2019, at: 16:00
Regular seats28
Activity Prices:
  - Industry/For-profit12,000.00 kr.
  - PhD student (Open Market Agreement, Nova, VLAG)4,500.00 kr.
ECTS credits5.50
Contact personHenriette Hansen    E-mail address: henha@food.ku.dk
Enrolment Handling/Course OrganiserLukasz Krych    E-mail address: krych@food.ku.dk
Teaching languageEnglish
Semester/BlockSpring
Scheme groupNot included in the scheme group
Scheme group noteDaily teaching hours: 8:30 - 16:30.
Exam formWritten assignment
Exam detailsEvaluation of written report (passed/not passed). Report must be delivered 3 weeks after the end of the course
Exam aidsAll aids allowed
Grading scalePassed / Not passed
Criteria for exam assessmentThere are two reports, a wet lab report and a dry-lab report, each one corresponding to 30 hours work.
Exam re-examinationfter agreement with course responsible.
Course workload
Course workload categoryHours
Lectures15.00
Laboratory20.00
Theory exercises20.00
Preparation25.00
Report writing30.00
Report writing30.00
Sum140.00
Aim and content
Adequate generation and analysis of DNA sequencing data should be a part of every (medicine-, research-, and industry-) scientist’s toolbox. In this short course, theory and hands-on sample preparation and DNA sequencing using 2nd (Illumina) and 3rd (Oxford Nanopores Technologies) generation sequencing technologies will be provided. As a core content of the course, participants will be able to process raw data (e.g. fast5/fastq) and use downstream software for mapping amplicons (e.g. 16S rRNA gene), re-constructing genomes, estimating abundance tables (e.g. OTU tables), and applying exploratory analysis (e.g. alpha- and beta-diversity) for factor/treatment associations.

Furthermore, through a supplementary section, attendees will be able to apply several univariate and multivariate analytical tools. These tools are typically needed to gain deeper understanding on microbiome (e.g. variable selection, size effect), and the linking of microbiome with other omics data.

The course is dedicated for PhD students and industry representatives. The course lasts for 5+(2) days. The main part (5 days) includes wet lab and introduction to basic data analysis (4 ECTS). Participants can choose to take part in two additional days (extra 1.5 ECTS) focusing on extended practical exercises on microbiome data analysis.

WHEN REGISTERING FOR THIS COURSE, YOU REGISTER FOR BOTH PART I AND PART II, i.e. FOR 5.5 ECTS.

• Introduction to 2nd (illumina) and 3rd (Oxford Nanopore Technologies, PacBio) generation DNA sequencing strategies.
• Wet-lab: library preparation for amplicon sequencing with illumina and Oxford Nanopore Technologies (ONT) sequencing and introduction to metagenome sequencing strategies.
• Introduction to data analysis: illumina and Oxford Nanopore Technologies based amplicon sequencing; introduction to ONT metagenome analysis and hybrid assembly (illumina & ONT).


Formel requirements
Students must bring their own laptops (unix based systems only: MAC OSX or Linux).

Learning outcome
Learning objectives - Part I (5 days, 4 ECTS)
The participant will be able to:
• Assess DNA quality and concentration with spectrophotometric and colorimetric methods.
• Build the sequencing libraries for barcoded 16S rRNA gene amplicon (v3 region) sequencing with illumina.
• Build the sequencing libraries for barcoded 16S rRNA gene amplicon (near full: v1-v9) sequencing with ONT.
• Built the sequencing library for ON-rep-seq.
• Prepare the DNA library to sequence with Oxford Nanopore Technologies.
• Load and flash MinION and PromethION flow cells.
• Analyse data from raw fastq (illumina) to generation of OTU-table (introduction to basic unix commands, QIIME2, and R).
• Analyse data from raw fast5 (ONT) to generation of OTU-table (introduction Albacore, Porechop and MinKNOW).
• Analyse data from ON-rep-seq for species-level identification and strain level discrimination of bacteria and yeast.
• Run de-novo assembly using illumina, ONT and hybrid-assembly ((meta)-spades, centrifuge, kraken, canu)

Learning objectives - Part II (2 days, 1.5 ECTS)
Participants joining the two additional days focusing on extended practical microbiome data analysis exercises will be able to:
• Reach a deeper understanding on microbiome data using multivariate analysis tools on real case examples.
• Perform alpha-diversity analysis and statistical tests to find differences in alpha diversity indices.
• Generate PCoA and nmds plots and perform statistics on distance matrices (UniFrac and non-UniFrac based).
• Perform differential abundance testing for differences in taxa between two or more categories (ANCOM, ANOVA, metagenomeSeq,)
• Apply Canonical Correlation Analysis (CCA) and Redundancy Analysis (RDA) to link response variables with the explanatory variables.
• Perform Discriminant Analysis (DA) with taxonomy agglomeration, multiple-testing in DA and multivariate DA (PLSDA).
• Perform multivariate analysis linking microbiome vs omics data (Canonical Correlation Analysis)


WHEN REGISTERING FOR THIS COURSE, YOU REGISTER FOR BOTH PART I AND PART II, i.e. FOR 5.5 ECTS.

Teaching and learning methods
The course consists of lectures, practical wet-lab and dry-lab exercises. Students will be able to get hands-on experience with ONT and Illumina libraries preparation techniques. The course includes a computer exercise where students will be able to analyze data.

Lecturers
Lukasz Krych
Associate professor, Department of Food Science, University of Copenhagen

Josue L. Castro-Mejia
Postdoc, Department of Food Science, University of Copenhagen

Dennis S. Nielsen
Professor, Department of Food Science, University of Copenhagen

Morten A. Rasmussen
Associate professor, Department of Food Science, University of Copenhagen

Duccio Cavalieri
Associate professor, Department of Biology, University of Florence

Remarks
The course fee is DKK 4,500 for students at Danish universities and VLAG and DKK 12,000 for all other participants. The course fee covers the cost of reagents and food (breakfast and lunch).

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