acdc - Automated Contamination Detection and Confidence estimation for single-cell genome data.

Journal: BMC bioinformatics
Published Date:

Abstract

BACKGROUND: A major obstacle in single-cell sequencing is sample contamination with foreign DNA. To guarantee clean genome assemblies and to prevent the introduction of contamination into public databases, considerable quality control efforts are put into post-sequencing analysis. Contamination screening generally relies on reference-based methods such as database alignment or marker gene search, which limits the set of detectable contaminants to organisms with closely related reference species. As genomic coverage in the tree of life is highly fragmented, there is an urgent need for a reference-free methodology for contaminant identification in sequence data.

Authors

  • Markus Lux
    Computational Methods for the Analysis of the Diversity and Dynamics of Genomes, Bielefeld University, Universitätsstr. 25, Bielefeld, 33615, Germany. mlux@techfak.uni-bielefeld.de.
  • Jan Krüger
    Center for Biotechnology - CeBiTec, Bielefeld University, Universitätsstr. 27, Bielefeld, 33615, Germany.
  • Christian Rinke
    School of Chemistry and Molecular Biosciences, Australian Centre for Ecogenomics, The University of Queensland, QLD 4072, Australia.
  • Irena Maus
    Center for Biotechnology - CeBiTec, Bielefeld University, Universitätsstr. 27, Bielefeld, 33615, Germany.
  • Andreas Schlüter
    Center for Biotechnology - CeBiTec, Bielefeld University, Universitätsstr. 27, Bielefeld, 33615, Germany.
  • Tanja Woyke
    , 2800 Mitchell Drive, Walnut Creek, 94598, CA, USA.
  • Alexander Sczyrba
    Center for Biotechnology - CeBiTec, Bielefeld University, Universitätsstr. 27, Bielefeld, 33615, Germany.
  • Barbara Hammer
    Librarian at Medical Library, University of Bergen, Bergen 5020, Norway.