Effects of Sample Size on Plant Single-Cell RNA Profiling.

Effects of Sample Size on Plant Single-Cell RNA Profiling.
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DOI:
10.3390/cimb43030119
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发表时间:
2021-10-20
影响因子:
3.1
通讯作者:
Guo L
Guo L
中科院分区:
生物学4区
文献类型:
--
作者:
Chen H;Lv Y;Yin X;Chen X;Chu Q;Zhu QH;Fan L;Guo L

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单细胞RNA(ScRNA)谱分析或scRNA测序(scRNA-seq)使并行研究给定植物组织中多种类型细胞的不同分子特征和发现细胞发育过程成为可能。在这项研究中,我们评估了样本大小(即细胞数量)对单细胞转录组分析结果的影响,方法是从从五项已发表的研究中整合的约57,000个拟南芥根细胞池中采样不同数量的细胞。结果表明,当样本细胞数为20,000-30,000个时,差异表达基因的主成分最显著,约20,000个细胞可获得较高的细胞聚类可靠性,细胞数越多,差异表达基因的识别效果越好,96%的差异表达基因可以在不超过20,000个细胞的情况下被成功识别,5000个细胞的亚样本可以估计出相对稳定的伪时间。最后,我们的结果为优化用于植物scRNA-seq研究的样本量提供了一般指导。
Single-cell RNA (scRNA) profiling or scRNA-sequencing (scRNA-seq) makes it possible to parallelly investigate diverse molecular features of multiple types of cells in a given plant tissue and discover cell developmental processes. In this study, we evaluated the effects of sample size (i.e., cell number) on the outcome of single-cell transcriptome analysis by sampling different numbers of cells from a pool of ~57,000 Arabidopsis thaliana root cells integrated from five published studies. Our results indicated that the most significant principal components could be achieved when 20,000–30,000 cells were sampled, a relatively high reliability of cell clustering could be achieved by using ~20,000 cells with little further improvement by using more cells, 96% of the differentially expressed genes could be successfully identified with no more than 20,000 cells, and a relatively stable pseudotime could be estimated in the subsample with 5000 cells. Finally, our results provide a general guide for optimizing sample size to be used in plant scRNA-seq studies.
从单细胞基因表达谱的细胞身份定量。
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