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通过最佳运输分析推断空间转录学的细胞轨迹

Xunan Shen¹, Lulu Zuo², Zhongfei Ye³

¹BGI Research, Chongqing 401329, China; BGI Research, Beijing 102601, China.

|February 4, 2025

概括

SpaTrack通过整合基因表达和空间转录学空间数据来重建细胞分化轨迹. 这种方法揭示了发育和疾病期间的细胞动态,推进了轨迹推断.

科学领域:

计算生物学计算生物学
基因组学就是基因组学.
发育生物学发展生物学

背景情况:

使用转录组学和空间位置来组织细胞分化轨迹是复杂的.
现有的方法很难将空间转录学数据有效地整合到谱系追踪中.

研究的目的:

开发一个新的计算框架,SpaTrack,用于重建细胞分化轨迹.
整合基因表达和空间位置数据,以准确推断血统.

主要方法:

SpaTrack利用最佳运输来将基因表达和空间坐标统一到过渡成本中.
它基于随着时间的推移而受到转录因子影响的表达特征来建模细胞命运.

主要成果:

SpaTrack成功地重建了详细的空间和时间细胞分化轨迹.
它准确地追踪了多个样本和时间间隔的细胞动态.
该方法确定了瘤中的恶性血统,包括那些经历了上皮细胞-介质细胞过渡和转移的瘤.

结论:

SpaTrack推进了空间转录组学数据的轨迹推断方法.
提供了对发育过程和疾病进展的关键见解,例如癌症转移.

关键词:

细胞分化的细胞分化.最佳的运输最佳的运输.空间转录学空间转录学轨迹推断的推断是指轨迹的推断.

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