Abstract Summary As DNA sequencing data is available for personal use, genomic privacy is becoming a major challenge. Nevertheless, high-throughput genomic data analysis outsourcing is performed using pipelines that tend to overlook these challenges. Results We present a client-server-based outsourcing framework for genotype imputation, an important step in genomic data analyses. Genotype data is encrypted by the client and encrypted data are used by the server that never observes the data in plain. Cloud-based framework can benefit from virtually unlimited computational resources while providing provable confidentiality. We demonstrate server’s utility from several aspects using genotype dataset from the 1000 Genomes datasets. First, we benchmark the accuracy of common variant imputation in comparison to BEAGLE, a state-of-the-art imputation method. We also provide the detailed time requirements of the server to showcase scaling of time usage in different steps of imputation. We also present a simple correlation metric that can be used to estimate imputation accuracy using only the reference panels. This is important for filtering the variants in downstream analyses. As a further demonstration and a different use case, we performed a simulated genomewide association study (GWAS) using imputed and known genotypes and highlight potential utility of the server for association studies. Overall, our study present multiple lines of evidence for usability of secure imputation service. Availability Server is publicly available at https://www.secureomics.org/OpenImpute . Users can anonymously test and use imputation server without registration. Contact Arif.O.Harmanci@uth.tmc.edu

Open Imputation Server provides secure Imputation services with provable genomic privacy