Event Date
This is a ‘LIVE COURSE’ – the instructor will be delivering lectures and coaching attendees through the accompanying computer practical’s via video link, a good internet connection is essential.
TIME ZONE – `Central European Standard Time (CET) – however all sessions will be recorded and made available allowing attendees from different time zones to follow.
Please email oliverhooker@prstatistics.com for full details or to discuss how we can accommodate you.
Metabarcoding has emerged as a pivotal technique, rapidly expanding and revolutionizing the way we study biodiversity. From soil samples to aquatic environments, metabarcoding provides insights into the diverse array of organisms present, offering crucial information for conservation efforts and ecological research. However, metabarcoding encounters intrinsic biases inherent in its methodology. Metabarcoding pipelines are designed to mitigate these biases, and this course will offer insights into optimizing these pipelines for accurate and reliable results. With new techniques continuously evolving, we’ll explore methodologies geared towards unraveling both inter and intra-species diversity while addressing the common challenges encountered in a methodology. Additionally, we’ll navigate the landscape of methods enabling comprehensive biodiversity assessments, alongside showcasing new machine learning approaches for inferring ecological quality status. This course will focus on the MJOLNIR3 pipeline and its theoretical framework. This R package is based on eight simple functions divided into four different blocks. For each function, a comprehensive description of the process will be provided, including alternatives from other pipelines and their basic command line usage.
By the end of the course, participants will:
Delivered remotely
Availability – 30 places
Duration – 5 days
Contact hours – Approx. 35 hours
ECT’s – Equal to 3 ECT’s
Language – English
Introductory lectures on the concepts and refreshers on R usage and linux command line. Intermediate-level lectures interspersed with hands-on mini practicals. Data sets for computer practicals will be provided by the instructors, but participants are welcome to bring their own data. Keep in mind that huge datasets can take hours of running time and subsets are recommended. Hands on will try to focus on the different format files to allow students to create their own pipelines.
A basic understanding of laboratory process. Basic knowledge of biodiversity analysis.
Basic familiarity with R and linux command line.
Participants must use a computer with a good internet connection, a working recent version or R (and ideally also RStudio), and recent versions of some R packages whose installation instructions will be sent a few days before the course. A working webcam is desirable for enhanced interactivity during the live sessions. Some computation power is required for modelling large datasets, although the provided example data (and suggested subsets of participants’ data) can run on an ordinary laptop.
PLEASE READ – CANCELLATION POLICY
Cancellations are accepted up to 28 days before the course start date subject to a 25% cancellation fee. Cancellations later than this may be considered, contact oliverhooker@prstatistics.com. Failure to attend will result in the full cost of the course being charged. In the unfortunate event that a course is cancelled due to unforeseen circumstances a full refund of the course fees will be credited.
If you are unsure about course suitability, please get in touch by email to find out more oliverhooker@prstatistics.com
Classes from 09:30 – 17:30 (CET)
DAY 1
– What is DNA metabarcoding and how to apply it to my research.
– Basic metabarcoding terminology
– Differences between sampling methods
– Differences between different target organisms. Universal and specific primers: their pros and limitations.
– COI and other markers.
– Identifying the different biases in laboratory processes. PCR, sequencing, contaminations, quimeras…
– How to manage increasing data volumes.
– Designing a Bias-Handling Strategy. Divide the pipeline in 4 stages:
1- Demultiplexing and initial filters
2- Units delimitation. From Denoising to clustering methods.
3- Taxonomic assignment
4- Final filtering steps
– Industrial assembly lines and Nordic mithology as a metaphores for Metabarcoding pipeline
– Get familiar with basic bash commands and R scripts.
Classes from 09:30 – 17:30 (CET)
DAY 2
– Presenting MJOLNIR3 pipeline, an R package to easy process metabarcoding data.
Getting started with MJOLNIR3 pipeline
– Understand the theory behind
– Presentation and installation of the required software; conda, obitools3, cutadapt, vsearch, DnoisE, SWARM, lulu and dada2.
– Demultiplexing, initial filtering steps, sequence quality, pairing and dereplication and quimera detection.
– Meet the gods RAN, FREYJA and HELA.
– Practical
Classes from 09:30 – 17:30 (CET)
Day 3
– Alternatives to RAN, FREYJA and HELA
– The dada2 approach.
– To denoise or to cluster.
– Choosing the strategy.
– Meet the god ODIN.
– Practical
– Alternatives to ODIN
Classes from 09:30 – 17:30
Day 4
– Alternatives to RAN, FREYJA and HELA
– The dada2 approach.
– To denoise or to cluster.
– Choosing the strategy.
– Meet the god ODIN.
– Hands on
– Alternatives to ODIN
Classes from 09:30 – 17:30
Day 5
– Taxonomic assignment
– Know the different reference databases
– Meet the god THOR
– ecotag, vsearch and other software
– Practical
– Alternatives to THOR
– Final filtering steps
– Meet the gods FRIGGA, LOKI and face the final battle at the RAGNAROC
– Practical
– Understand the three levels of metabarcoding pipelines. How we go from command line and MJOLNIR3 package to the graphical user interfaces with SLIM as example
Coming soon…