scTranslation: A Comprehensive Benchmark for Single-Cell Multi-Omics Modality Translation 文章

ArXiv CS.AI2026-06-03NEWSen作者: Jiabei Cheng, Jingbo Zhou, Jun Xia, Changkai Li, Zhen Lei, Chang Yu, Stan Z. Li

摘要

arXiv:2606.03906v1 Announce Type: new Abstract: Simultaneous measurement of multiple omics modalities in single cells enables researchers to gain a more comprehensive understanding of cellular states and regulatory mechanisms. However, due to high experimental costs, significant noise, and incomplete modality coverage, a variety of computational methods for modality translation have emerged in recent years. Despite the development of translation models, there is still a lack of systematic benchmark evaluation in terms of datasets, evaluation metrics, and influencing factors. To address this, we present scTranslation, a comprehensive benchmark for single-cell multi-omics modality translation tasks. It includes diverse translation datasets, integrates state-of-the-art models, and provides a comprehensive evaluation metrics. In addition, we assess model performance under different scenarios, such as feature selection, feature quality, and few-shot settings.

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