An Approach to Compression of Genomic Data Based on Image File Format

The reduction in cost, sequencing time and assembly of thousands of complete genomes imposed an increasing demand for genomic data storage. Data compression approaches are viable solutions to circumvent such a demand and can reduce genetic data by more than 75% of the needed space amount of uncompressed information. Current specialized strategies implemented as compression tools for DNA sequences take advantage of the inherent characteristics of the DNA sequences, such as the small size of the required alphabet (ATCG) for data representation as well as the frequency of internal repeats in a sequence. In this work, we explore a novel perspective for lossless genomic sequence compression using standard lossless image formats. We show that DNA sequences stored in a FASTA file are converted into a matrix of bits. The matrix was then encoded in the lossless image file formats WEBP and FLIF for performance evaluation. It was performed using a dataset containing 1,547 DNA sequences from 1,163 different organisms from the kingdoms Animalia, Archaea, Bacteria, Fungi, Plant, and Protist. Our results demonstrated that the WEBP format presented the best space savings (76.15%, ±0.84) when compared to the other image formats. Furthermore, when compared to specialized genomic data compression tools, WEBP space savings presented similar results with DELIMINATE (76.03%, ±2.54) and MFCOMPRESS (76.97%, ±1.36).