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首页> 外文期刊>BMC Genomics >Choice of pre-processing pipeline influences clustering quality of scRNA-seq datasets
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Choice of pre-processing pipeline influences clustering quality of scRNA-seq datasets

机译：选择预处理管道的选择影响Scrna-SEQ数据集的聚类质量

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Single-cell RNA sequencing (scRNA-seq) has quickly become one of the most dominant techniques in modern transcriptome assessment. In particular, 10X Genomics’ Chromium system, with its high throughput approach, turn key and thorough user guide made this cutting-edge technique accessible to many laboratories using diverse animal models. However, standard pre-processing, including the alignment and cell filtering pipelines might not be ideal for every organism or tissue. Here we applied an alternative strategy, based on the pseudoaligner kallisto, on twenty-two publicly available single cell sequencing datasets from a wide range of tissues of eight organisms and compared the results with the standard 10X Genomics’ Cell Ranger pipeline. In most of the tested samples, kallisto produced higher sequencing read alignment rates and total gene detection rates in comparison to Cell Ranger. Although datasets processed with Cell Ranger had higher cell counts, outside of human and mouse datasets, these additional cells were routinely of low quality, containing low gene detection rates. Thorough downstream analysis of one kallisto processed dataset, obtained from the zebrafish pineal gland, revealed clearer clustering, allowing the identification of an additional photoreceptor cell type that previously went undetected. The finding of the new cluster suggests that the photoreceptive pineal gland is essentially a bi-chromatic tissue containing both green and red cone-like photoreceptors and implies that the alignment and pre-processing pipeline can affect the discovery of biologically-relevant cell types. While Cell Ranger favors higher cell numbers, using kallisto results in datasets with higher median gene detection per cell. We could demonstrate that cell type identification was not hampered by the lower cell count, but in fact improved as a result of the high gene detection rate and the more stringent filtering. Depending on the acquired dataset, it can be beneficial to favor high quality cells and accept a lower cell count, leading to an improved classification of cell types.
机译：单细胞RNA测序（ScRNA-SEQ）迅速成为现代转录组评估中最占主导地位的技术之一。特别是10X基因组学的铬系统，具有其高通量方法，转动钥匙和彻底的用户指南使得这种前沿技术可以使用不同的动物模型来访问许多实验室。然而，标准预处理，包括对准和细胞过滤管道可能对每个生物或组织都不理想。在这里，我们应用了一种基于伪aligner kallisto的替代策略，其来自八种生物的各种组织的二十二个公共单细胞测序数据集，并将结果与​​标准的10x基因组学的细胞系列管道进行了比较。在大多数经过测试的样品中，Kallisto与细胞游器相比，Kallisto产生了更高的测序读取对准速率和总基因检测速率。尽管用细胞游器处理的数据集具有更高的细胞计数，但在人和小鼠数据集之外，这些额外的细胞是低质量的，含有低基因检测速率。从斑马鱼松果腺中获得的一个Kallisto加工数据集的彻底下游分析显示更清晰的聚类，允许识别先前未被发现的额外的感光细胞类型。新群体的发现表明，光接收的松弛腺本质上是含有绿色和红色锥形光感受器的双色组织，并且意味着对准和预处理管道可以影响生物学相关细胞类型的发现。虽然Cell Ranger在较高的细胞编号上，使用Kallisto导致具有较高中位基因检测的数据集每种细胞。我们可以证明细胞型鉴定不会受到较低的细胞计数阻碍，但实际上由于高基因检测率和更严格的滤波而改善。取决于所收购的数据集，有利于高质量的细胞并接受较低的细胞计数，导致细胞类型的分类改进。

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