Leveraging data-driven self-consistency for high-fidelity gene expression recovery
oleh: Md Tauhidul Islam, Jen-Yeu Wang, Hongyi Ren, Xiaomeng Li, Masoud Badiei Khuzani, Shengtian Sang, Lequan Yu, Liyue Shen, Wei Zhao, Lei Xing
| Format: | Article |
|---|---|
| Diterbitkan: | Nature Portfolio 2022-11-01 |
Deskripsi
Recovering dropout-affected gene expression values is a challenging problem in bioinformatics. Here, the authors propose a data-driven framework, that first learns the underlying data distribution and then recovers the expression values by imposing a self-consistency on the expression matrix.