Bioinformatics

Bioinformatics

CCRI Bioinformatics Team

The bioinformatics team provides advice and support for CCRI researchers with regard to analysis, integration and interpretation of large scale genomics datasets. We maintain and run computational pipelines for processing raw next-generation sequencing (NGS) data and data quality checks for all genomics data held within the CCRI/St.Anna Children´s Hospital. We are also performing high quality data analyses in close collaboration with CCRI/St.Anna Children´s Hospital researchers in the following thematic areas:

  • Variant analyses (small variants, SVs, CNVs, fusions) in genomics data (WGS, WES, low-coverage WGS, targeted sequencing, array technologies)
  • Transcriptomics (RNA-Seq, scRNA-Seq)
  • Epigenomics (WGBS, ChIP-Seq, ATAC-Seq)
  • Functional genomics (integrated analyses of the above)
  • Database and scientific software development and maintenance

We are furthermore conducting translational bioinformatics research in cooperation with CCRI researchers and external professionals.

Staff

Gerda Modarres

After working in diagnostics in a cytogenetics laboratory as medical-technical assistant for several years, I decided in 2008 to do a Master’s degree in Bioinformatics in extra-occupational studies at FH-Campus-Wien. While still studying, I changed my job in 2013 to work in the bioinformatics field. I started to work for ACIB and did analyses in functional genomics and proteomics for biotechnological research projects. In 2016 I joined the CCRI where I am now developing a database and an application to link different queries for laboratory results for projects and studies.

Dagmar Schinnerl

I am a Postdoc in the Genetics of Leukemia Group and have a profound background in life sciences due to my master thesis at the University of Technology and my PhD in molecular biology and genetics, which I conducted at the CCRI. During this time I started with bioinformatics analysis of microarray and next generation sequencing data (in particular RNAseq and ChIPseq). Combining wet lab experiments with data analysis gives me the unique opportunity to shape research projects from beginning to end.

Florian Kromp

While working at the IT department of the St. Anna Kinderspital and studying Medical Informatics at the TU Wien, I started my scientific career in the department of immunological diagnostics working on the automation of B-Cell-ALL MRD analysis using flow cytometry and unsupervised machine learning methods. During my Master’s degree, I started to focus on biomedical image analysis of neuroblastoma tumors, specializing in supervised machine learning and, in particular, deep learning methods for an automated segmentation of fluorescence microscopy images. In addition to image segmentation, I developed pipelines to analyse antibody expression of cellular populations using fluorescence microscopy. Recently, I have started to work as technical coordinator of the FFG project VISIOMICS, focusing on the integration of multiOMICs datasets including the application of bioinformatics and statistics approaches, data visualisation and visual analytics methods.

Former members

  • Niko Popitsch
  • Maximilian Kauer
  • Murat Tugrul
  • Christian Frech (Seven Bridges Genomics)

Selected Articles

Software

  • VARAN-GIE (since 2018) is an extension to the IGV genome browser that adds functionality to curate and annotate sets of genomic intervals. By this, VARAN supports an integrative approach to viewing and annotating large genomic data sets.
  • RG (since 2016) is a method for partitioning genomes into regions that can be genotyped with high/low confidence.
  • ARGOS (since 2014) is pipeline for extracting signals from a genomic sequence that characterize its repetitiveness.
  • CODOC (since 2014) is a format and API for the efficient representation and processing of depth-of-coverage data (complementing formats such as TDF or BigWig). It supports highly-efficient lossless and lossy data compression.