小柯机器人

美国哈佛医学院Allon M. Klein研究组取得一项新成果。他们开发了连贯稀疏优化方法 (CoSpar) -一种从单细胞转录组和谱系信息中识别早期细胞命运偏差的方法。2022年2月21日出版的《自然—生物技术》杂志发表了这项成果。

他们开发了CoSpar作为一种稳健的计算方法，用于从与谱系追踪集成的单细胞转录组学推断细胞动力学。基于转换图的连贯性和稀疏性假设，CoSpar 对严重的降采样和谱系数据的分散具有鲁棒性，这使得实验设计更简单，并且需要更少的校准。在代表造血、重编程和定向分化的数据集中，CoSpar 识别出以前未检测到的早期命运偏差，预测与命运选择有关的转录因子和受体。常见实验设计的文档和详细示例可在 https://cospar.readthedocs.io/网站获得。

据介绍，单细胞全基因组分析的目标是重建细胞分化、疾病发作和药物反应期间的动态转变。单细胞分析最近已与谱系追踪相结合，这是一组识别共同祖先细胞以建立细胞状态之间真实动态关系的方法。这些综合方法揭示了未被重视的细胞动力学，但它们的分析面临着由嘈杂、分散的谱系数据引起的反复挑战。

附：英文原文

Title: CoSpar identifies early cell fate biases from single-cell transcriptomic and lineage information

Author: Wang, Shou-Wen, Herriges, Michael J., Hurley, Kilian, Kotton, Darrell N., Klein, Allon M.

Issue&Volume: 2022-02-21

Abstract: A goal of single-cell genome-wide profiling is to reconstruct dynamic transitions during cell differentiation, disease onset and drug response. Single-cell assays have recently been integrated with lineage tracing, a set of methods that identify cells of common ancestry to establish bona fide dynamic relationships between cell states. These integrated methods have revealed unappreciated cell dynamics, but their analysis faces recurrent challenges arising from noisy, dispersed lineage data. In this study, we developed coherent, sparse optimization (CoSpar) as a robust computational approach to infer cell dynamics from single-cell transcriptomics integrated with lineage tracing. Built on assumptions of coherence and sparsity of transition maps, CoSpar is robust to severe downsampling and dispersion of lineage data, which enables simpler experimental designs and requires less calibration. In datasets representing hematopoiesis, reprogramming and directed differentiation, CoSpar identifies early fate biases not previously detected, predicting transcription factors and receptors implicated in fate choice. Documentation and detailed examples for common experimental designs are available at https://cospar.readthedocs.io/ . A computational algorithm integrates lineage tracing with single-cell RNA sequencing and improves early cell fate prediction.

DOI: 10.1038/s41587-022-01209-1

Source: https://www.nature.com/articles/s41587-022-01209-1

Nature Biotechnology：《自然—生物技术》，创刊于1996年。隶属于施普林格·自然出版集团，最新IF：68.164
官方网址：https://www.nature.com/nbt/
投稿链接：https://mts-nbt.nature.com/cgi-bin/main.plex