{"ID":3004678,"CreatedAt":"2026-06-03T03:09:48.883664427Z","UpdatedAt":"2026-06-05T11:43:53.432517148Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2606.03906","arxiv_id":"2606.03906","title":"scTranslation: A Comprehensive Benchmark for Single-Cell Multi-Omics Modality Translation","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. These factors significantly affect model performance but have rarely been systematically studied before. Leveraging this benchmark, we conduct a large-scale study of current methods, report many insightful findings that open up new possibilities for future development. The benchmark is open-sourced to facilitate future research. The code is anonymously released at https://github.com/Bunnybeibei/scTranslation.","short_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...","url_abs":"https://arxiv.org/abs/2606.03906","url_pdf":"https://arxiv.org/pdf/2606.03906v1","authors":"[\"Jiabei Cheng\",\"Jingbo Zhou\",\"Jun Xia\",\"Changkai Li\",\"Zhen Lei\",\"Chang Yu\",\"Stan Z. Li\"]","published":"2026-06-02T17:00:49Z","proceeding":"cs.AI","tasks":"[\"cs.AI\"]","methods":"[]","has_code":false,"code_links":[{"ID":612693,"CreatedAt":"2026-06-03T03:09:48.883664427Z","UpdatedAt":"2026-06-03T03:09:48.883664427Z","DeletedAt":null,"paper_id":3004678,"paper_url":"https://arxiv.org/abs/2606.03906","paper_title":"scTranslation: A Comprehensive Benchmark for Single-Cell Multi-Omics Modality Translation","repo_url":"https://github.com/Bunnybeibei/scTranslation","is_official":false,"mentioned_in_paper":false,"mentioned_in_github":true,"github_stars":0}]}