A Reliable and Secure Method for Sharing Genomic Data

Genomics has significantly impacted the field of medicine, with advances in DNA sequencing leading to personalized medicine and a deeper understanding of the genomic basis of various diseases. The ability to share genomic data is crucial for advancing this field and developing new approaches to understanding the genome. However, the sensitive nature of this data requires secure methods for protecting it during storage and transfer. In this paper, we present a new tool for the secure encryption and decryption of FASTA files without sharing a common secret and with a reduced number of shared keys between the pairs. Our proposal combines symmetric and asymmetric encryption techniques, including the AES (Advanced Encryption Standard) cypher and RSA (Rivest-Shamir-Adleman). The tool is fast, reliable, and secure, outperforming existing tools in terms of security and ease of use. This makes it a valuable solution for the secure sharing and use of sensitive genomic data, representing a significant advancement in the field of genomics.

MZPAQ: a FASTQ data compression tool

Background

Due to the technological progress in Next Generation Sequencing (NGS), the amount of genomic data that is produced daily has seen a tremendous increase. This increase has shifted the bottleneck of genomic projects from sequencing to computation and specifically storing, managing and analyzing the large amount of NGS data. Compression tools can reduce the physical storage used to save large amount of genomic data as well as the bandwidth used to transfer this data. Recently, DNA sequence compression has gained much attention among researchers.

Results

In this paper, we study different techniques and algorithms used to compress genomic data. Most of these techniques take advantage of some properties that are unique to DNA sequences in order to improve the compression rate, and usually perform better than general-purpose compressors. By exploring the performance of available algorithms, we produce a powerful compression tool for NGS data called MZPAQ. Results show that MZPAQ outperforms state-of-the-art tools on all benchmark datasets obtained from a recent survey in terms of compression ratio. MZPAQ offers the best compression ratios regardless of the sequencing platform or the size of the data.

Conclusions

Currently, MZPAQ's strength is its higher compression ratio as well as its compatibility with all major sequencing platforms. MZPAQ is more suitable when the size of compressed data is crucial, such as long-term storage and data transfer. More efforts will be made in the future to target other aspects such as compression speed and memory utilization.