In the research area Immunology we focus on the description and research of the human adaptive immune system.The human adaptive immune system plays a vital role in the detection of potential pathogens, diseases that are difficult or impossible to cure, such as various types of cancer and autoimmune diseases. We also rely on the functionality of our immune system during transplantation processes.One of the main tasks here is the identification and description of the components and signal pathways which lead to a specific immune reaction or which differ in diseased and supposedly healthy individuals. This makes an important contribution to the explainability of various diseases and the development of new, innovative therapies.The latest technologies in molecular biology generate large amounts of data that have to be analyzed efficiently. We here mainly deal with the analysis of genetic data. This includes the analysis of gene expressions, database analyses and the identification of mutations. The main focus is on diseases such as leukemia, but also organ rejection reactions and infectionswith various pathogens such as Helicobacter pylori.Since 2012, we have been developing the ImmunExplorer software, which enables algorithms for the analysis of the human immune repertoire, the immunoglobulins and T-cell receptors, from blood and tissue data. An extensive expansion and continuation of ImmunExplorer, namely ImmunoDataAnalyzer, will be published soon in 2020. In close cooperation with our partners at MedUni Vienna, AKH Vienna, University of Salzburg and the Hospital of the Barmherzigen Brüder we strive to advance the research area and intensify national and international cooperation.
|2019||Roman Reindl-Schwaighofer, Julia Vetter, Johannes Weinberger, Susanne Schaller, Andreas Heinzel, Guido Gualdoni, Constantin Aschauer, Kira Jelencsics, Karin Hu, Stephan M. Winkler, and Rainer Oberbauer:||T-Cell Repertoire of Tissue Infiltrating T-cells at Time of Rejection||American Transplant Congress 2019|
Our Implementation for Point Mutation Identification (IMPI) platform is a stand-alone software and implements algorithms which allow UMI tagged NGS data processing and the analysis of minor allele frequencies (MAFs).
The software is compatible with Windows 10 and Linux 20.04 LTS operating systems. The software is implemented in Python 3.7 and allows for automated processing and evaluation of NGS data. The developed tool focuses on the detection and identification of point mutations and provides information about the allele frequencies (AF). IMPI provides individual parameter settings and condition definition for processing single and multiple UMI tagged NGS data files. The main methods implemented in IMPI are data cleaning, extracting UMIs, building consensus sequences and providing position weight matrices (PWMs) for point mutation identification. Additionally, parameter optimization algorithms are implemented for the automated detection of parameter settings to determine which ones fits best to a data set.
IMPI was initially developed for the identification of low frequency resistance mutations in chronic myeloid leukemia (CML) patients for early relapse detection. Data derived from a custom-designed highly sensitive NGS approach developed at the Ordensklinikum Linz, Barmherzige Schwestern.
Susanne Schaller MMSc
Susanne Schaller MMSc
Julia Vetter MSc
Prof.(FH) PD DI Dr. Stephan Winkler
2019 - present
University of Applied Sciences Upper Austria, Hagenberg, Austria
Ordensklinikum Linz, Barmherzige Schwestern, Linz, Austria