Tag Archives: Metagenomics

Metagenomics: from bench to data analysis

Metagenomics: from bench to data analysis

Date: Monday 19 September to Friday 23 September 2016
Venue: Earlham Institute, Norwich, United Kingdom

Application Deadline: 15 July 2016

Participation: Open application, with selection process

Registration fee: £300.00 which is inclusive of lunch and
refreshments, course dinner and course materials.
Accommodation and transport from/to hotel to Earlham Institute will be an optional extra during
registration if you are selected for the course.

To provide an overview of the main aspects involved in metagenomics from the bench to data analysis and discussion around the interpretation and actual examples of the impact and applications of metagenomics derived research.

Registration: https://www.eiseverywhere.com/ereg/newreg.php?eventid=178239&

Organiser: Emily Angiolini

Registration deadline: 15 July 2016

Cost: £300.00

Bursaries: There are bursaries available for DEANN members upon application and successful selection to be used to cover registration and to put towards travel and/or accommodation as appropriate.

Enquiries: TGAC Training Team

Scientific Organisers:

  • Emily Angiolini, The Genome Analysis Centre (TGAC), UK
  • Kirsten McLay, The Genome Analysis Centre (TGAC), UK
  • Leah Catchpole, The Genome Analysis Centre (TGAC), UK
  • Richard Leggett, The Genome Analysis Centre (TGAC), UK
  • Mark Alston, The Genome Analysis Centre (TGAC), UK

What is the workshop about? A substantial part of the course will be devoted to bioinformatics resources and tools relevant in metagenomics data analysis. Participants will start at the bench and end in front of the computers for a problem solving activity utilizing the bioinformatics training they will be receiving during the course.

What will it cover? To provide an overview of the main aspects involved in metagenomics from the bench to data analysis and discussion around the interpretation and actual examples of the impact and applications of metagenomics derived research.

What will I learn?

  • An overview of NGS for metagenomics and metatranscriptomics including current projects
  • Knowledge of 16S Experimental Design including primer design and sources of error
  • Hands on experience in: DNA isolation, QC of the DNA, NGS library construction and loading the sequencing platform
  • An overview of software for analysis and interpretation of metagenomics datasets and some basic analytical workflows
  • Hands-on experience of a case study dataset including FastQC, trimming and host removal
  • Understanding assembly principles and the latest metagenomics assembly tools
  • Hands on experience in metagenomics assembly
  • Using MEGAN to explore metagenomic and metatranscriptomic data including taxonomic and functional annotation, multiple comparison methods and production of publication quality images
  • An overview and hands on experience in public data resources for metagenomics e.g. IMG/M, EBI Metagenomics, MG-RAST

Target Audience: This course is aimed at advanced PhD students and post-doctoral researchers who are doing or planning to start research in the field of metagenomics.

Programme: http://www.earlham.ac.uk/metagenomics-bench-data-analysis-2016#Programme-2 

 

Article: MetLab: An In Silico Experimental Design, Simulation and Analysis Tool for Viral Metagenomics Studies

journal.pone.0160334.g001

journal.pone.0160334.g002

Abstract

Metagenomics, the sequence characterization of all genomes within a sample, is widely used as a virus discovery tool as well as a tool to study viral diversity of animals. Metagenomics can be considered to have three main steps; sample collection and preparation, sequencing and finally bioinformatics. Bioinformatic analysis of metagenomic datasets is in itself a complex process, involving few standardized methodologies, thereby hampering comparison of metagenomics studies between research groups. In this publication the new bioinformatics framework MetLab is presented, aimed at providing scientists with an integrated tool for experimental design and analysis of viral metagenomes. MetLab provides support in designing the metagenomics experiment by estimating the sequencing depth needed for the complete coverage of a species. This is achieved by applying a methodology to calculate the probability of coverage using an adaptation of Stevens’ theorem. It also provides scientists with several pipelines aimed at simplifying the analysis of viral metagenomes, including; quality control, assembly and taxonomic binning. We also implement a tool for simulating metagenomics datasets from several sequencing platforms. The overall aim is to provide virologists with an easy to use tool for designing, simulating and analyzing viral metagenomes. The results presented here include a benchmark towards other existing software, with emphasis on detection of viruses as well as speed of applications. This is packaged, as comprehensive software, readily available for Linux and OSX users at https://github.com/norling/metlab.

Full article in the following link