T2 – Computational Mass Spectrometry with OpenMS – From Algorithms to Integrated Workflows

 

Date: Saturday September 8, 2018

Time: 9:00 – 17:00

Venue: Stavros Niarchos Foundation Cultural Center

Room: Computer Room

 

Short Description

Computational mass spectrometry provides important tools and bioinformatic solutions for the analysis of proteomics and metabolomics data. Non-targeted methods are ideal for unbiased discovery studies and scale well for large-scale studies (e.g., clinical proteomics/metabolomics). This de.NBI training event introduces key concepts of non-targeted label-free analysis and workflow-based processing using real-life datasets. We will introduce several open-source software tools for proteomics, primarily focusing on OpenMS (www.OpenMS.org). In a hands-on session, we will demonstrate how to combine these tools into complex data analysis workflows including visualization of the results. Participants will have the opportunity to bring their own data and design custom analysis workflows together with instructors. If requested by participants, we can also guide in implementing novel methods or tool into the OpenMS framework.

Training material and handouts will be prepared for both users that want to design proteomic workflows, as well as training material for algorithm and tool developers.

 

Learning goals:

Capabilities of the OpenMS library and tools; How these tools are combined in flexible and powerful workflows to analyze LC-MS based, high-throughput proteomic data; How the powerful workflow engine KNIME is employed to build these workflows and visualize results.

 

Prerequisites:

Basic knowledge of MS based proteomics

 

Keywords:

LC-MS based proteomics, OpenMS, workflows, KNIME, data analysis

 

Tools:

OpenMS, KNIME

 

Schedule:

9:00-10:30    Introduction to OpenMS and KNIME (hands-on)

11:00-12:30  Peptide Identification (hands-on)

13:30-15:00  Label-free quantification Part I (hands-on)

15:30-17:00  Label-free quantification Part II (hands-on)

 

Contact:

Scientific and program questions: sachsenb@informatik.uni-tuebingen.de