生物
计算生物学
细胞谱系
多样性(政治)
谱系(遗传)
细胞
再生(生物学)
细胞分化
基因
发育生物学
进化生物学
遗传学
人类学
社会学
作者
Gunsagar S. Gulati,Shaheen S. Sikandar,Daniel J. Wesche,Anoop Manjunath,Anjan Bharadwaj,Mark J. Berger,Francisco Ilagan,Angera H. Kuo,Robert W. Hsieh,Shang Cai,Maider Zabala,Ferenc A. Scheeren,Neethan A. Lobo,Dalong Qian,Feiqiao Brian Yu,Frederick M. Dirbas,Michael F. Clarke,Aaron M. Newman
出处
期刊:Science
[American Association for the Advancement of Science]
日期:2020-01-24
卷期号:367 (6476): 405-411
被引量:956
标识
DOI:10.1126/science.aax0249
摘要
More diversity at the top A detailed knowledge of cell differentiation hierarchies is important for understanding diverse biological processes such as organ development, tissue regeneration, and cancer. Single-cell RNA sequencing can help elucidate these hierarchies, but it requires reliable computational methods for predicting cell lineage trajectories. Gulati et al. developed CytoTRACE, a computational framework based on the simple observation that transcriptional diversity—the number of genes expressed in a cell—decreases during differentiation. CytoTRACE outperformed other methods in several test cases and was successfully applied to study cellular hierarchies in healthy and tumor tissue. Science , this issue p. 405
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