pQuant

pQuant employs homomorphic encryption to enable privacy-preserving quantification of gene expression from RNA-seq data.

Key Features:

• Privacy-preserving computation: pQuant performs computations on encrypted data, allowing researchers to handle sensitive information without exposing it.
• Accuracy: pQuant achieves accuracy comparable to state-of-the-art non-secure algorithms like STAR and kallisto.
• Scalability: pQuant is highly scalable and its runtime and memory do not depend on the number of reads.
• Parallel processing: pQuant supports parallel processing to enhance efficiency regardless of the number of genes analyzed.

Scientific Applications:

• Secure gene expression quantification: pQuant enables privacy-preserving quantification of gene expression from RNA-seq data across public and cloud servers.
• Protection of sensitive genotypes: pQuant prevents exposure of private genotypes of individuals during RNA-seq computation.

Methodology:

pQuant employs homomorphic encryption to perform computations on encrypted RNA-seq data.