DigestiFlow - reproducible demultiplexing for the single cell era
1
Core Unit Bioinformatics, Berlin Institute of Health, Berlin, Germany
2
Charité – Universitätsmedizin Berlin, Berlin, Germany
3
Max Delbrück Center for Molecular Medicine, Berlin, Germany
- Published
- Accepted
- Subject Areas
- Bioinformatics, Computational Science
- Keywords
- next-generation sequencing, demultiplexing, scientific data management
- Copyright
- © 2019 Holtgrewe et al.
- Licence
- This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Preprints) and either DOI or URL of the article must be cited.
- Cite this article
- 2019. DigestiFlow - reproducible demultiplexing for the single cell era. PeerJ Preprints 7:e27717v2 https://doi.org/10.7287/peerj.preprints.27717v2
Abstract
An ever-increasing number of NGS library preparation protocols used in biomedical research requires complex barcoding schemes. In combination with the economic urge to use deep multiplexing on high volume sequencing devices this has turned the once mundane task of demultiplexing into a complex and error prone analysis step. We present an easy to implement, efficient, flexible, and extendable open source solution to address this challenge. All software is available under the permissive MIT open source license.
Author Comment
Extended the manuscript with more details about the method.
Supplemental Information
Digestiflow Server Documentation
The documentation of Digestiflow at the time of publication. An up-to-date version is available online. The link can be found on the project page on GitHub.