Title | Time | Room | Teacher |
---|---|---|---|
Introduction to analysing microbial genomics and multi'omics data | 15.06.2023 09:00 - 16:30 (Thu) | Seminar-room at Graduate Center of Life Sciences | Dr. Melanie Schirmer |
Introduction to analysing microbial genomics and multi'omics data | 16.06.2023 09:00 - 16:30 (Fri) | Seminar-room at Graduate Center of Life Sciences | Dr. Melanie Schirmer |
Date: 15.06. + 16.06.2023
Time: 09:00 - 16:30
Location: Seminarroom at Graduate Center of Life Sciences, Alte Akademie 8a, 85354 Freising
The aim of this two-day workshop is to provide a thorough introduction to computational
approaches for the analysis of sequencing data from microbial samples. The course will be focused
on metagenomic data from microbial communities. We will explain how taxonomic and functional
profiles are generated from raw sequencing data, introduce different bioinformatic approaches to
process sequencing data, followed by multivariate statistical analyses and different visualization
techniques. We will also cover different approaches to assemble whole genome sequencing data from
short and long read sequencing. Overall, the course will consist of a mixture of lectures and
hands-on tutorials.
By the end of the course participants will:
1. Be familiar with different workflows involved in the analysis of large-scale multi-omics studies.
2. Understand how to generate taxonomic and functional profiles from metagenomic sequencing data.
3. Be familiar with applying a multivariable statistical framework to generate hypotheses and account
for confounding covariates.
4. Be able to use exploratory data visualizations techniques and visualize results from the statistical
analysis using R.
5. Be familiar with the assembly of whole genome sequencing data for bacterial isolates.
Intended audience:
Master and PhD students who want to learn computational approaches for the analysis
of high-dimensional sequencing data. Attendees are assumed to have a basic understanding
of microbial community studies. Familiarity with the R is an advantage. We will also offer a short
introductory lab for R to make the course more accessible to a wider audience.