Toward universal immunofluorescence normalization for multiplex tissue imaging with UniFORM
7.5
来源：
Cell
关键字：
neural coding
发布时间：
2025-09-09 03:33
摘要：
UniFORM is a novel, non-parametric normalization pipeline for multiplex tissue imaging (MTI) data, addressing the challenges of technical variations in staining intensity. It employs an automated rigid landmark registration method to align signal distributions while preserving biological signals. Benchmarked against existing methods, UniFORM shows superior performance in batch correction and biological integrity preservation across various cancer datasets. This advancement is crucial for accurate biological interpretations and enhances the potential for clinical applications in oncology.
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关键证据
UniFORM consistently outperforms existing methods in mitigating batch effects while maintaining biological signal fidelity.
The method is benchmarked against three MTI platforms, demonstrating its robustness.
UniFORM's automated approach allows for effective normalization without prior distributional assumptions.
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AI评分总结
UniFORM is a novel, non-parametric normalization pipeline for multiplex tissue imaging (MTI) data, addressing the challenges of technical variations in staining intensity. It employs an automated rigid landmark registration method to align signal distributions while preserving biological signals. Benchmarked against existing methods, UniFORM shows superior performance in batch correction and biological integrity preservation across various cancer datasets. This advancement is crucial for accurate biological interpretations and enhances the potential for clinical applications in oncology.