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Data-driven batch detection enhances single-cell omics data analysis

delete2024-10-01
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PRE
AI
Z
Ziqi Zhang
X
Xiuwei Zhang *
DOI：10.1016/j.cels.2024.09.011delete
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Abstract

Abstract

En 中文
In single-cell omics studies, data are typically collected across multiple batches, resulting in batch effects: technical confounders that introduce noise and distort data distribution. Correcting these effects is challenging due to their unknown sources, nonlinear distortions, and the difficulty of accurately assigning data to batches that are optimal for integration methods.

Journal

Cell Systems cover
Cell Systems
IF:
7.7
Papers:
1.4K
Citations:
1.0W

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