NSCPHD1171  Molecular Community Analysis

Volume 2014/2015
Content

Recent years have seen an enormous increase in publications based on NGS amplicon data and much emphasis has been put into the bioinformatic treatment of data i.e. de-noising and OTU assignment.  Extracting the community signal from the obtained OTU matrix is next important step in the process, and the focus of this course. The modern community ecological tool box includes many advanced tools and great developments have been achieved in recent years within this field - now often termed ecoinfomatics. This course mainly addresses PhD students who already have generated sequence-based OTU data.  

The course focuses on hands-on data analysis. Therefore the bulk of the course time is allocated to participants’ work on their own data under expert guidance. We will supply accompanying “standard datasets” if participants would like to explore types of analysis that their own data are not suited for.

  • Data types, input and transformation. Ways to explore species/OTU richness and diversity (α-diversity)
  • Rank-abundance patterns and models
  • Comparisons across communities (β-diversity). Distance measures, ordination and correlation with meta-data
  • Permutation tests
  • Variation partitioning
  • GLS models and use of AICs
  • Functional groups and analysis in trait space, trait dispersion
  • Phylogenetic dispersion
  • Ways to analyze spatial community turnover, optimization of sampling protocols
  • Complementary lectures on Design of ecological studies sampling communities, Sampling and processing different types of substrate for molecular analysis, OTU assignment and Current state of next generation sequencing techniques

 

Sunday

Monday

Tuesday

Wednesday

Thursday

Friday

Saturday

Arrival

Lecture:

Computerlab:

Lecture:

Computerlab:

Lecture:

Computerlab:

Lecture:

Computerlab:

Lecture:

Computerlab:

Departure

Lunch

Lunch

Lunch

Lunch

Lunch

Lecture:

Computerlab:

Lecture:

Computerlab:

Lecture:

Computerlab:

Lecture:

Computerlab:

Student presentations of results:

Evening mixer

Diner and student presentations

Evening free

Evening free

Evening free

Course diner

 

Learning Outcome

Participants are, after the course, expected to be able to thoroughly analyze their own datasets and think critically on published and own data and data analysis.   

The course are limited to 20 participants so priority will be given to PhD students who are in their initial phase of analyzing their own data. Depending on interest, we will admit other participants.
Basic knowledge of R-based packages recommended but not required.

Participants sought: The students we seek for to this course are students working with meta-barcoding of eukaryote communities. We strongly recommend that you bring your own NGS-generated community dataset. Note that this course will not directly include how to define OTUs from sequence data i.e. the bioinformatics tools for this.
Lectures and Computer labs with provided and own data (most of the time is allocated for the latter). Student presentations (Flash talks second evening and presentation of obtained results last day)
Food
Lunch is included all days. Dinner/snacks is included the first (Sunday), second (Tuesday) and last evening (Friday).
Travel, accommodation and reimbursement

Accommodation in Copenhagen are self-organized. Cheaper possibilities are International House (https:/​/​adobeformscentral.com/​?f=obplZ-NE-GelHW7mK3-Hfg) which offers special rates for UCPH guests (use link). Otherwise, the cheapest hotel possibilities are CABINN (https:/​/​www.cabinn.com/​en/​). Three main hostels in Copenhagen (http:/​/​www.danhostel.dk/​en) and B&Bs ( http:/​/​www.copenhagenbedandbreakfast.dk/​CopenhagenKortGB.htm)
Up to 10 students from outside the Copenhagen/Lund area can be reimbursed for some travel expenses (max 1500 DKK) and accommodation expenses (max 1500 DKK).
Credit
3 ECTS
Type of assessment
Course participation under invigilation
  • Category
  • Hours
  • Preparation
  • 30
  • Lectures
  • 10
  • Practical Training
  • 45
  • Total
  • 85