DNA Bloom Filter enables anti-contamination and file version control for DNA-based data storage

Brief Bioinform. 2024 Mar 27;25(3):bbae125. doi: 10.1093/bib/bbae125.ABSTRACTDNA storage is one of the most promising ways for future information storage due to its high data storage density, durable storage time and low maintenance cost. However, errors are inevitable during synthesizing, storing and sequencing. Currently, many error correction algorithms have been developed to ensure accurate information retrieval, but they will decrease storage density or increase computing complexity. Here, we apply the Bloom Filter, a space-efficient probabilistic data structure, to DNA storage to achieve the anti-error, or anti-contamination function. This method only needs the original correct DNA sequences (referred to as target sequences) to produce a corresponding data structure, which will filter out almost all the incorrect sequences (referred to as non-target sequences) during sequencing data analysis. Experimental results demonstrate the universal and efficient filtering capabilities of our method. Furthermore, we employ the Counting Bloom Filter to achieve the file version control function, which significantly reduces synthesis costs when modifying DNA-form files. To achieve cost-efficient file version control function, a modified system based on yin-yang codec is developed.PMID:38555478 | DOI:10.1093/bib/bbae125

Source: Briefings in Bioinformatics - March 30, 2024 Category: Bioinformatics Authors: Yiming Li Haoling Zhang Yuxin Chen Yue Shen Zhi Ping Source Type: research