The performance of Federated Harmony on three types of single cell data.

Each row represents results of a type of data. scRNA-seq data (first row); mouse brain tissue spatial transcriptomics data (second row); scATAC-seq data (third row). For a-c, the upper plot is the iLISI density plot, the lower one is the UMAP. a: iLISI...

Full description

Saved in:

Bibliographic Details
Main Author:	Ruizhi Yuan (16864629) (author)
Other Authors:	Ziqi Rong (22339789) (author), Haoran Hu (6032510) (author), Tianhao Liu (4678147) (author), Shiyue Tao (11871368) (author), Wei Chen (23863) (author), Lu Tang (655389) (author)
Published:	2025
Subjects:	Microbiology Genetics Biotechnology Infectious Diseases Plant Biology Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified xlink "> large based data integration approach preserves privacy introduce federated harmony raising privacy federated learning data sources various types security concerns often confounded harmony algorithm downstream analysis distributed multi cell multi
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!

The performance of Federated Harmony on three types of single cell data.

Similar Items