The main focus of the group is the development of algorithms and tools for the analysis of next-generation sequencing (NGS) data. The recent advances in high-throughput sequencing technologies led to an enormous increase in the amount of data generated. Furthermore, steadily improving and newly emerging technologies require a continuous adaptation of existing software. In many cases dedicated software has to be developed to efficiently handle and analyze the vast amount of sequencing data. While a few processing steps like quality control and mapping are quite independent of the sequencing application (e.g. ChIP-seq, re-sequencing), for each application specific software is needed to address the questions of interest.
Therefore, the group put strong emphasis on setting up an efficient processing infrastructure that allows to cope with sequencing data even for large cohorts of samples in a short time period. As a basic requirement for mutation screening and transcriptome analysis we developed and published comprehensive tool sets for variant detection and transcript expression analysis, respectively. Our processing and data management pipeline is an essential prerequisite to successfully address questions in e.g. cancer genomics or diagnostics where large sample numbers have to be analyzed. All algorithms developed in the group were optimized and validated experimentally in collaboration with the respective laboratories (Ropers, Yaspo). As a result of these tight interactions we published not only new algorithms but also their application to large-scale projects that otherwise could not have been tackled.