Sequence analysis and decoding with extra low-quality reads for DNA data storage.

Abstract

Error detection/correction codes play an important role to reduce writing and/or reading costs in DNA data storage. Sequence analysis algorithms also make a crucial effect on error correction but have been executed independently from the decoding of error correction codes. In conventional sequence analysis, low-quality reads are usually discarded. For DNA data storage, low-quality reads can be constructively used to sequence analysis with the assistance of error detection/correction codes. We obtained the low-quality reads which failed to pass the chastity filter in Illumina NGS sequencing. We confirmed the effectiveness of the extra low-quality reads by providing error statistics and performing decoding with them. We proposed a sequence clustering algorithm for various-length reads and a consensus algorithm based on probabilistic majority and error detection to efficiently exploit the extra reads. The proposed methods reduced the reading cost by 6.83% on average and up to 19.67% while maintaining the writing cost. https://github.com/PParkJy/SAD-DNAstorage (10.5281/zenodo.15571858).