research-article

scAEQN: A Batch Correction Joint Dimension Reduction Method on scRNA-seq Data

Authors:

Yansen SuAuthors Info & Claims

BIC '23: Proceedings of the 2023 3rd International Conference on Bioinformatics and Intelligent Computing

Pages 344 - 350

https://doi.org/10.1145/3592686.3592748

Published: 31 May 2023 Publication History

Abstract

As single cell sequencing technique continues to advance, the size of scRNA-seq dataset has been enlarging, generating batch effects that affect downstream analysis, such as clustering analysis and differential expression gene (DEG) analysis. In this context, we present a novel batch integration joint dimensionality reduction method titled scAEQN. It adopts QuantNorm to calculate coefficient matrix and constructs an autoencoder to estimate the matrix of coefficient, ultimately obtaining a low-dimensional representation and reconstruction of the data. scAEQN is compared to different batch correction methods on a simulated dataset and six real single-cell RNA datasets. The results suggest that scAEQN is superior to batch correction methods under comparison in downstream analysis. scAEQN effectively eliminates batches and strongly reserves clustering pattern of cells, providing solid back-up for downstream analyses. scAEQN enhances the capability of clustering and selects more representative and stable DEGs in differential expression gene analysis. The source code and supplementary information of scAEQN are provided on website https://github.com/SiningSong/scAEQN.

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Cited By

Di ZYang BLi MWu YJi H(2024)Batch effects correction in scRNA-seq based on biological-noise decoupling autoencoder and central-cross lossComputational Biology and Chemistry10.1016/j.compbiolchem.2024.108261113(108261)Online publication date: Dec-2024
https://doi.org/10.1016/j.compbiolchem.2024.108261

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BIC '23: Proceedings of the 2023 3rd International Conference on Bioinformatics and Intelligent Computing

February 2023

398 pages

ISBN:9798400700200

DOI:10.1145/3592686

Copyright © 2023 ACM.

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Published: 31 May 2023

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BIC 2023

BIC 2023: 2023 3rd International Conference on Bioinformatics and Intelligent Computing

February 10 - 12, 2023

Sanya, China

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Cited By

Di ZYang BLi MWu YJi H(2024)Batch effects correction in scRNA-seq based on biological-noise decoupling autoencoder and central-cross lossComputational Biology and Chemistry10.1016/j.compbiolchem.2024.108261113(108261)Online publication date: Dec-2024
https://doi.org/10.1016/j.compbiolchem.2024.108261

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