Coding and processing of high-throughput sequencing data

TNT members involved in this project:
Dr.-Ing. Marco Munderloh
Prof. Dr.-Ing. Jörn Ostermann
Dipl.-Ing. Jan Voges

Over the past years, technological advances in sequencing (i.e., the process of reading out genomic information) have led to a faster and more cost-efficient approach to sequence individual genomes. Because of the enormous amount of sequencing data generated by high-throughput sequencing (HTS) machines, the processing, storage, and analysis of sequencing data entails novel challenges for the scientific community. Novel processes and tools have to be developed to overcome the current limitations in terms of storage space, processing speed, and many more.

Raw sequencing data generated by HTS machines passes through a great number of different analysis steps. Our goal is to develop novel algorithms to enhance the information processing "from the tissue to the hard drive".

Show all publications
  • Jan Voges, Jörn Ostermann, Mikel Hernaez
    CALQ: compression of quality values of aligned sequencing data
    Bioinformatics (Advance article btx737), Oxford University Press, November 2017, edited by Bonnie Berger
  • Claudio Alberti, Jan Voges
    Study on ISO/IEC 23092-2 WD 3
    ISO/IEC JTC 1/SC 29/WG 11, Document Number M41393, Macao (CN), October 2017
  • Jan Voges
    Core Experiment 5 on Genomic Information Representation results LUH
    ISO/IEC JTC 1/SC 29/WG 11, Document Number M40804, Turin (IT), July 2017