Two-Stage Alignment Framework for Batch Effect Removal and Cell Type Classification in ScRNA-seq
Author:
Affiliation:
1. Nanjing University of Aeronautics and Astronautics,College of Computer Science and Technology,Nanjing,China
Funder
Research and Development
National Natural Science Foundation of China
Fundamental Research Funds for the Central Universities
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10528382/10528383/10528562.pdf?arnumber=10528562
Reference30 articles.
1. scReClassify: post hoc cell type classification of single-cell rNA-seq data
2. SCEC: A Novel Single-Cell Classification Method Based on Cell-Pair Ensemble Learning
3. Semisupervised adversarial neural networks for single-cell classification
4. scDeepSort: a pre-trained cell-type annotation method for single-cell transcriptomics using deep learning with a weighted graph neural network
5. Reference-based analysis of lung single-cell sequencing reveals a transitional profibrotic macrophage
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