Singapore Immunology Network, Agency for Science, Technology and Research, Singapore, Singapore.
Shanghai Institute of Immunology, Shanghai JiaoTong University School of Medicine, Shanghai, China.
Front Immunol. 2018 Oct 23;9:2425. doi: 10.3389/fimmu.2018.02425. eCollection 2018.
In recent years there has been a rapid increase in the use of single-cell sequencing (scRNA-seq) approaches in the field of immunology. With the wide range of technologies available, it is becoming harder for users to select the best scRNA-seq protocol/platform to address their biological questions of interest. Here, we compared the advantages and limitations of four commonly used scRNA-seq platforms in order to clarify their suitability for different experimental applications. We also address how the datasets generated by different scRNA-seq platforms can be integrated, and how to identify unknown populations of single cells using unbiased bioinformatics methods.
近年来,单细胞测序(scRNA-seq)方法在免疫学领域的应用迅速增加。随着各种技术的广泛应用,用户越来越难以选择最佳的 scRNA-seq 方案/平台来解决他们感兴趣的生物学问题。在这里,我们比较了四种常用的 scRNA-seq 平台的优缺点,以阐明它们在不同实验应用中的适用性。我们还讨论了如何整合来自不同 scRNA-seq 平台的数据集,以及如何使用无偏生物信息学方法识别未知的单细胞群体。
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