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RepairNatrix: a Snakemake workflow for processing DNA sequencing data for DNA storage.
Schwarz, Peter Michael; Welzel, Marius; Heider, Dominik; Freisleben, Bernd.
Afiliação
  • Schwarz PM; Department of Mathematics and Computer Science, University of Marburg, Marburg 35032, Germany.
  • Welzel M; Department of Mathematics and Computer Science, University of Marburg, Marburg 35032, Germany.
  • Heider D; Department of Mathematics and Computer Science, University of Marburg, Marburg 35032, Germany.
  • Freisleben B; Department of Mathematics and Computer Science, University of Marburg, Marburg 35032, Germany.
Bioinform Adv ; 3(1): vbad117, 2023.
Article em En | MEDLINE | ID: mdl-38496344
ABSTRACT
Motivation 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 reproducible results.

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 25-35 across different datasets. Availability and implementation RepairNatrix is available on Github https//github.com/umr-ds/repairnatrix.

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Alemanha

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Alemanha