deepMNN: Deep Learning-Based Single-Cell RNA Sequencing Data Batch Correction Using Mutual Nearest Neighbors

deepMNN: Deep Learning-Based Single-Cell RNA Sequencing Data Batch Correction Using Mutual Nearest Neighbors

It is well recognized that batch effect in single-cell RNA sequencing (scRNA-seq) data remains a big challenge when integrating different datasets. Here, we proposed deepMNN, a novel deep learning-based method to correct batch effect in scRNA-seq data. We first searched mutual nearest neighbor (MNN)...

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Bibliographic Details
Main Authors: Bin Zou, Tongda Zhang, Ruilong Zhou, Xiaosen Jiang, Huanming Yang, Xin Jin, Yong Bai
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-08-01
Series:Frontiers in Genetics
Subjects:
scRNA-seq data integration
batch effect correction
residual network
mutual nearest neighbor
deep learning
Online Access:https://www.frontiersin.org/articles/10.3389/fgene.2021.708981/full

Internet

https://www.frontiersin.org/articles/10.3389/fgene.2021.708981/full

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