New publication!

Our new article has been accepted in Bioinformatics Advances:

Schwarz PM, Welzel M, Heider D, Freisleben B: RepairNatrix – a Snakemake workflow for processing DNA sequencing data for DNA storage. Bioinformatics Advances 2023, in press. (Link)


There has been rapid progress in the development of error-correcting and constrained codes for DNA storage systems in recent years. However, improving the steps for processing raw sequencing data for DNA storage has a lot of untapped potential for further progress. In particular, constraints can be used as prior information to improve the processing of DNA sequencing data. Furthermore, a workflow tailored to DNA storage codes enables fair comparisons between different approaches while leading to reproducable results.

We present RepairNatrix, a read-processing workflow for DNA storage. RepairNatrix supports preprocessing of raw sequencing data for DNA storage applications and can be used to flag and heuristically repair constraint-violating sequences to further increase the recoverability of encoded data in the presence of errors. Compared to a preprocessing strategy without repair functionality, RepairNatrix reduced the number of raw reads required for the successful, error-free decoding of the input files by a factor of 25 to 35 across different datasets.

RepairNatrix is available on Github:

Written by: Dominik Heider