Effects of Sample Size on Plant Single-Cell RNA Profiling
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 nu...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2021-10-01
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| Series: | Current Issues in Molecular Biology |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1467-3045/43/3/119 |
| Summary: | 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 <i>Arabidopsis thaliana</i> 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. |
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| ISSN: | 1467-3037 1467-3045 |