用Smmit整合多个单细胞多组学样本。

Changxin Wan, Zhicheng Ji
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引用次数: 0

摘要

多样本单细胞多组学数据集同时测量同一细胞和多个样本中的多种数据模式,有助于在群体规模上研究基因表达和基因调控活性。现有的集成方法可以集成多个样本或多个模态,但不能同时集成两者。为了解决这一限制,我们开发了Smmit,这是一种计算管道,利用现有的集成方法来同时集成样本和模态,并生成降维的统一表示。我们展示了Smmit在两个真实数据集中集成样本和模态信息的能力,同时保留细胞类型差异。Smmit是一个在Github上免费提供的R软件包:https://github.com/zji90/Smmit.
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Integrating multiple single-cell multi-omics samples with Smmit.

Integrating multiple single-cell multi-omics samples with Smmit.

Multi-sample single-cell multi-omics datasets, which simultaneously measure multiple data modalities in the same cells across multiple samples, facilitate the study of gene expression, gene regulatory activities, and protein abundances on a population scale. We developed Smmit, a computational method for integrating data both across samples and modalities. Compared to existing methods, Smmit more effectively removes batch effects while preserving relevant biological information, resulting in superior integration outcomes. Additionally, Smmit is more computationally efficient and builds upon existing computational pipelines, requiring minimal effort for implementation. Smmit is an R software package that is freely available on Github: https://github.com/zji90/Smmit.

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