Gama, N. | bioRxiv Science

bioRxiv2025

UC Irvine Brain Initiative Cell Atlas Network (BICAN) Brain Procurement Program for the Center for Multiomic Human Brain Cell Atlas Project

High-quality neurotypical postmortem human brain tissue is essential but difficult to obtain for constructing comprehensive human brain cell atlases. Here we describe the establishment of UC Irvines Brain Procurement Program, a coordinated initiative to collect and process neurotypical donor brains for multiomic mapping studies within the NIH BRAIN Initiative Cell Atlas Network (BICAN) consortium. Through partnerships with the Orange County Coroners Office, the UC Irvine Willed Body Program, UCI Medical Center, and the Childrens Hospital of Orange County, we have developed standardized workflows encompassing donor identification, postmortem brain recovery and processing, region-of-interest dissection, neurotypical donor selection, and data management. Our experience demonstrates the feasibility of a community-based, multi-institutional procurement framework while highlighting challenges in recruiting neurotypical donors and ensuring demographic representation reflective of Southern California. We further identify opportunities to strengthen outreach and donation pathways. This program provides a scalable model for advancing population-reflective, high-quality human brain cell atlas efforts. HighlightsO_LIEstablish a multi-site pipeline for procuring high-quality neurotypical human brains. C_LIO_LIDemonstrate feasibility of donor collection across childhood to adulthood. C_LIO_LIIdentify barriers and propose strategies to improve broad donor recruitment. C_LI

neuroscience↗

bioRxiv2020

Ultra-Fast Homomorphic Encryption Models enable Secure Outsourcing of Genotype Imputation

ABSTRACTGenotype imputation is a fundamental step in genomic data analysis such as GWAS, where missing variant genotypes are predicted using the existing genotypes of nearby ‘tag’ variants. Imputation greatly decreases the genotyping cost and provides high-quality estimates of common variant genotypes. As population panels increase, e.g., the TOPMED Project, genotype imputation is becoming more accurate, but it requires high computational power. Although researchers can outsource genotype imputation, privacy concerns may prohibit genetic data sharing with an untrusted imputation service. To address this problem, we developed the first fully secure genotype imputation by utilizing ultra-fast homomorphic encryption (HE) techniques that can evaluate millions of imputation models in seconds. In HE-based methods, the genotype data is end-to-end encrypted, i.e., encrypted in transit, at rest, and, most importantly, in analysis, and can be decrypted only by the data owner. We compared secure imputation with three other state-of-the-art non-secure methods under different settings. We found that HE-based methods provide full genetic data security with comparable or slightly lower accuracy. In addition, HE-based methods have time and memory requirements that are comparable and even lower than the non-secure methods. We provide five different implementations and workflows that make use of three cutting-edge HE schemes (BFV, CKKS, TFHE) developed by the top contestants of the iDASH19 Genome Privacy Challenge. Our results provide strong evidence that HE-based methods can practically perform resource-intensive computations for high throughput genetic data analysis. In addition, the publicly available codebases provide a reference for the development of secure genomic data analysis methods.Competing Interest StatementThe authors have declared no competing interest.View Full Text

bioinformatics↗