Federated privacy-protected meta- and mega-omics data analysis in multi-center studies with a fully open-source analytic platform.

The importance of maintaining data privacy and complying with regulatory requirements is highlighted especially when sharing omic data between different research centers. This challenge is even more pronounced in the scenario where a multi-center effort for collaborative omics studies is necessary. OmicSHIELD is introduced as an open-source tool aimed at overcoming these challenges by enabling privacy-protected federated analysis of sensitive omic data. In order to ensure this, multiple security mechanisms have been included in the software. This innovative tool is capable of managing a wide range of omic data analyses specifically tailored to biomedical research. These include genome and epigenome wide association studies and differential gene expression analyses. OmicSHIELD is designed to support both meta- and mega-analysis, so that it offers a wide range of capabilities for different analysis designs. We present a series of use cases illustrating some examples of how the software addresses real-world analyses of omic data. Author summary: OmicSHIELD revolutionizes the way researchers can engage with federated omics data, providing a secure framework for conducting different omic data analyses. This innovative platform allows data to stay in their original repositories, thus eliminating data transfer—a crucial feature in an era where data privacy regulations are becoming increasingly stringent. By leveraging advanced techniques like differential privacy, OmicSHIELD aims to mitigate disclosure risks associated with analysis of omics data, while still enabling accurate collaborative research. The platform is highly flexible, supporting processing and analysis of multiple omic data formats. This makes it a useful tool for researchers looking to perform complex analyses across multiple datasets. OmicSHIELD includes active disclosure control checks and the ability to compute a wide range of analytical methods useful to obtain insights from omic data. By prioritizing both analytical power and data privacy, OmicSHIELD addresses the most pressing challenges in omics research today, making it easier for scientists to unlock new insights while maintaining high ethical standards. [ABSTRACT FROM AUTHOR]