Metatranscriptomics analysis using microbiome RNA-seq data in Galaxy

Metatranscriptomics analysis using microbiome RNA-seq data in Galaxy

advanced bioinformatics
online
omics
basic bioinformatics
ELIXIR
Location:

Online

Start date:

25 May 2021

Duration:

Afternoon session

General context

Metatranscriptomics analysis examines how the microbiome responds to the environment by studying the taxonomic composition and functional analysis of genes expressed by the microbiome, using microbial community RNASeq data and subsequent metatranscriptomics workflows. This workshop will introduce researchers to the basic concepts and tools from the ASaiM-MT workflow. ASaiM-MT provides a curated collection of tools to explore and visualize taxonomic and functional information from metatranscriptomic sequences.

The workshop trainers will update attendees on the latest developments in Galaxy tools and workflows for functional microbiome and multi-omics analysis.

Objectives
  • Choose the best approach to analyze metatranscriptomics data

  • Understand the functional microbiome characterization using metatranscriptomic results

  • Understand where metatranscriptomics fits in ‘multi-omic’ analysis of microbiomes

  • Visualise a community structure

Required skills

No prior bioinformatics knowledge is required, however a basic understanding of the Galaxy platform and metatranscriptomics experiments is definitely helpful to get more out of the course. 

Trainers

Pratik Jagtap
Co-lead GalaxyP & Research Assistant Professor at Department of Biochemistry, Molecular Biology and Biophysics (University of Minnesota)

Pratik Jagtap is a Research Assistant Professor at the Department of Biochemistry, Molecular Biology and Biophysics at the University of Minnesota. He has helped manage the Galaxy-P project from its inception. His research interests include developing analytical workflows for analysis of complex data, with particular emphasis on MS-based proteomics applications in metaproteomics, proteogenomics and data-independent acquisition (DIA) data analysis.  

Subina Mehta
GalaxyP Team Member & Researcher at Department of Biochemistry, Molecular Biology and Biophysics (University of Minnesota)

Subina Mehta is a researcher in the Griffin Lab at the Department of Biochemistry, Molecular Biology and Biophysics at the University of Minnesota. Her current research interests include developing analytical workflows, maintaining and debugging tools, developing training materials and help integrating tools within the Galaxy platform for analysis of MS-based proteomics data and its applications in proteomics, metaproteomics and proteogenomics study. 

Tim Griffin
Professor - Department of Biochemistry, Molecular Biology and Biophysics (University of Minnesota)
Faculty Director - Center for Mass Spectrometry and Proteomics (University of Minnesota)

Tim Griffin's research interests are in the development and application of analytical and bioinformatics tools, focused on biological mass spectrometry integrated with other 'omic data. His laboratory seeks to apply these multi-omic tools to advancing research related to important questions in biomedicine and basic understanding of biological systems. 

Magnus Arntzen
Norwegian University of Life Sciences, NO

Magnus Arntzen is a researcher in meta-omics analysis, specifically integrating quantitative techniques to retrieve relative expression levels in large datasets and correlate this with functional annotations, both in data from single species and mixed microbial communities. 

Saskia Hiltemann
Erasmus Medical Center, Rotterdam (NL)

Saskia Hiltemann works as a bioinformatician at the EMC, where she mainly works with the Galaxy analysis platform, creating tools and pipelines for the institute's researchers, and also performing her own data analysis, currently primarily focused on microbiota research. She is also strongly involved in trainings with Galaxy, and one of the co-founders of the Galaxy Training Materials framework. 

Program

Introduction to functional microbiome analysis
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Metatranscriptomics analysis using Galaxy framework
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Resources available for microbiome analysis and Q&A
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