Asset Details
Do you wish to reserve the book?
Harmony-based data integration for distributed single-cell multi-omics data
Hey, we have placed the reservation for you!
By the way, why not check out events that you can attend while you pick your title.
Oops! Something went wrong.
Looks like we were not able to place the reservation. Kindly try again later.
Are you sure you want to remove the book from the shelf?
Harmony-based data integration for distributed single-cell multi-omics data
Do you wish to request the book?
Harmony-based data integration for distributed single-cell multi-omics data
Please be aware that the book you have requested cannot be checked out. If you would like to checkout this book, you can reserve another copy
We have requested the book for you!
Your request is successful and it will be processed during the Library working hours. Please check the status of your request in My Requests.
Oops! Something went wrong.
Looks like we were not able to place your request. Kindly try again later.
Journal Article
Harmony-based data integration for distributed single-cell multi-omics data
2025
Overview
Large-scale single-cell projects generate rapidly growing datasets, but downstream analysis is often confounded by data sources, requiring data integration methods to do correction. Existing data integration methods typically require data centralization, raising privacy and security concerns. Here, we introduce Federated Harmony, a novel method combining properties of federated learning with Harmony algorithm to integrate decentralized omics data. This approach preserves privacy by avoiding raw data sharing while maintaining integration performance comparable to Harmony. Experiments on various types of single-cell data showcase superior results, highlighting a novel data integration approach for distributed multi-omics data without compromising data privacy or analytical performance.
Publisher
Public Library of Science,PLOS,Public Library of Science (PLoS)
Subject
/ Analysis
/ Computational Biology - methods
/ Computer and Information Sciences
/ Datasets
/ Genomics
/ Humans
/ Information Dissemination - methods
/ Medicine and Health Sciences
/ Methods
/ Privacy
/ Research and Analysis Methods
/ Single-Cell Analysis - methods
/ Single-Cell Analysis - statistics & numerical data
/ Tissues
